basic+programming+system

1) Business: basic software

2) Automation: basic programming support, basic programming system

Basic Control Engineering Programming System — система программирования на языке БЕЙСИК технических методов управления

SUBJECT AREA: Electronics and information technology

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Kurtz took his first degree in mathematics at the University of California in Los Angeles (UCLA), where he also gained experience in numerical methods as a result of working in the National Bureau of Standards Institute for Numerical Analysis located on the campus. In 1956 he obtained a PhD in statistics at Princeton, after which he took up a post as an instructor at Dartmouth College in Hanover, New Hampshire. There he found a considerable interest in computing was already in existence, and he was soon acting as the Dartmouth contact with the New England Regional Computer Center at Massachusetts Institute of Technology, an initiative partly supported by IBM. With Kemeny, he learned the Share Assembly Language then in use, but they were concerned about the difficulty of programming computers in assembly language and of teaching it to students and colleagues at Dartmouth. In 1959 the college obtained an LGP-30 computer and Kurtz became the first Director of the Dartmouth Computer Center. However, the small memory (4 k) of this 30-bit machine precluded its use with the recently available high-level language Algol 58. Therefore, with Kemeny, he set about developing a simple language and operating system that would use simple English commands and be easy to learn and use. This they called the Beginners All-purpose Symbolic Instruction Code (BASIC). At the same time they jointly supervised the design and development of a time-sharing system suitable for college use, so that by 1964, when Kurtz became an associate professor of mathematics, they had a fully operational BASIC system; by 1969 a sixth version was already in existence. In 1966 Kurtz left Dartmouth to become a Director of the Kiewit Computer Center, and then, in 1975, he became a Director of the Office of Academic Computing; in 1978 he returned to Dartmouth as Professor of Mathematics. He also served on various national committees.

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1 only, one-time, one, single.

2 unique, one-of-a-kind, single, unusual.

3 single, azygos, that is not one of a pair.

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► adjetivo

1 (solo) only, sole

■ la única persona the only person

■ lo único es que... the thing is...

2 (extraordinario) unique

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   1) Programs and the Complexity of Human Mental Processes

   In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)

   2) Artificial Intelligence Is an Engineering Discipline

   Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)

   3) A Sceptical View of Artificial Intelligence

   Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....

   When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)

   4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, Eventually

   Just as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)

   5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the Program

   Many problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)

   6) The Meaning of a Symbolic Description

   What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)

   7) The Principle of Artificial Intelligence

   [AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)

   8) Artificial Intelligence Recognizes the Need for Knowledge in Its Systems

   The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)

   9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract Form

   The basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)

    10) There Are Many Types of Reasoning

   There are many different kinds of reasoning one might imagine:

    Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."

    Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)

    11) Programs Are Beginning to Do Things That Critics Have Asserted to Be Impossible

   Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)

    12) The Synthesis of Man and Machine

   Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)

    13) The Thesis of Good Old-Fashioned Artificial Intelligence (GOFAI)

   The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)

    14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory Formation

   It is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)

    15) Four Kinds of Artificial Intelligence

   We might distinguish among four kinds of AI.

   ♦ Nonpsychological AI

   Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.

   ♦ Weak Psychological AI

   Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.

   ♦ Strong Psychological AI

... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)

   ♦ Suprapsychological AI

   Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)

    16) Determination of Relevance of Rules in Particular Contexts

   Even if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)

    17) Form and Content Are Not Fundamentally Different

   Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)

    18) The Assumption That the Mind Is a Formal System

   Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)

    19) A Statement of the Primary and Secondary Purposes of Artificial Intelligence

   The primary goal of Artificial Intelligence is to make machines smarter.

   The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)

    20) Mathematical Logic Provides the Basis for Theory in AI

   The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....

   AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)

    21) Perceptual Structures Can Be Represented as Lists of Elementary Propositions

   In artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)

    22) Definitions of Artificial Intelligence

   Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)

    23) The Computer Can Not Be a Model of the Mind

   Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)

    24) Computers Will Not Always Be Inferior to Human Brains

   The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)

   1) The Book of Nature Is Written in the Language of Mathematics

   Philosophy is written in that great book, the universe, which is always open, right before our eyes. But one cannot understand this book without first learning to understand the language and to know the characters in which it is written. It is written in the language of mathematics, and the characters are triangles, circles, and other figures. Without these, one cannot understand a single word of it, and just wanders in a dark labyrinth. (Galileo, 1990, p. 232)

   2) Arranging Speech so as to Reply Appropriately

   It never happens that it [a nonhuman animal] arranges its speech in various ways in order to reply appropriately to everything that may be said in its presence, as even the lowest type of man can do. (Descartes, 1970a, p. 116)

   3) No Other Animal Has the Language Capacity of the Human

   It is a very remarkable fact that there are none so depraved and stupid, without even excepting idiots, that they cannot arrange different words together, forming of them a statement by which they make known their thoughts; while, on the other hand, there is no other animal, however perfect and fortunately circumstanced it may be, which can do the same. (Descartes, 1967, p. 116)

   4) Human Beings Do Not Live Only in the World of Objects

   Human beings do not live in the object world alone, nor alone in the world of social activity as ordinarily understood, but are very much at the mercy of the particular language which has become the medium of expression for their society. It is quite an illusion to imagine that one adjusts to reality essentially without the use of language and that language is merely an incidental means of solving specific problems of communication or reflection. The fact of the matter is that the "real world" is to a large extent unconsciously built on the language habits of the group.... We see and hear and otherwise experience very largely as we do because the language habits of our community predispose certain choices of interpretation. (Sapir, 1921, p. 75)

   5) Language Powerfully Conditions All Our Thinking

   It powerfully conditions all our thinking about social problems and processes.... No two languages are ever sufficiently similar to be considered as representing the same social reality. The worlds in which different societies live are distinct worlds, not merely the same worlds with different labels attached. (Sapir, 1985, p. 162)

   6) A List of Language Games

   [A list of language games, not meant to be exhaustive:]

   Giving orders, and obeying them- Describing the appearance of an object, or giving its measurements- Constructing an object from a description (a drawing)Reporting an eventSpeculating about an eventForming and testing a hypothesisPresenting the results of an experiment in tables and diagramsMaking up a story; and reading itPlay actingSinging catchesGuessing riddlesMaking a joke; and telling it

   Solving a problem in practical arithmeticTranslating from one language into another

   LANGUAGE Asking, thanking, cursing, greeting, and praying-. (Wittgenstein, 1953, Pt. I, No. 23, pp. 11 e-12 e)

   7) Language Constrains Certain Modes of Interpretation

   We dissect nature along lines laid down by our native languages.... The world is presented in a kaleidoscopic flux of impressions which has to be organized by our minds-and this means largely by the linguistic systems in our minds.... No individual is free to describe nature with absolute impartiality but is constrained to certain modes of interpretation even while he thinks himself most free. (Whorf, 1956, pp. 153, 213-214)

   8) We Dissect Nature in Accordance with Our Native Languages

   We dissect nature along the lines laid down by our native languages.

   The categories and types that we isolate from the world of phenomena we do not find there because they stare every observer in the face; on the contrary, the world is presented in a kaleidoscopic flux of impressions which has to be organized by our minds-and this means largely by the linguistic systems in our minds.... We are thus introduced to a new principle of relativity, which holds that all observers are not led by the same physical evidence to the same picture of the universe, unless their linguistic backgrounds are similar or can in some way be calibrated. (Whorf, 1956, pp. 213-214)

   9) The Forms of a Person's Thoughts Are Controlled by Unperceived Patterns of His Own Language

   The forms of a person's thoughts are controlled by inexorable laws of pattern of which he is unconscious. These patterns are the unperceived intricate systematizations of his own language-shown readily enough by a candid comparison and contrast with other languages, especially those of a different linguistic family. (Whorf, 1956, p. 252)

    10) The Analysis of Certain Types of Utterances

   It has come to be commonly held that many utterances which look like statements are either not intended at all, or only intended in part, to record or impart straightforward information about the facts.... Many traditional philosophical perplexities have arisen through a mistake-the mistake of taking as straightforward statements of fact utterances which are either (in interesting non-grammatical ways) nonsensical or else intended as something quite different. (Austin, 1962, pp. 2-3)

    11) The Dictionary of a Language Is a System of Concepts

   In general, one might define a complex of semantic components connected by logical constants as a concept. The dictionary of a language is then a system of concepts in which a phonological form and certain syntactic and morphological characteristics are assigned to each concept. This system of concepts is structured by several types of relations. It is supplemented, furthermore, by redundancy or implicational rules..., representing general properties of the whole system of concepts.... At least a relevant part of these general rules is not bound to particular languages, but represents presumably universal structures of natural languages. They are not learned, but are rather a part of the human ability to acquire an arbitrary natural language. (Bierwisch, 1970, pp. 171-172)

    12) Talk about the Evolution of the Language Capacity is Beside the Point

   In studying the evolution of mind, we cannot guess to what extent there are physically possible alternatives to, say, transformational generative grammar, for an organism meeting certain other physical conditions characteristic of humans. Conceivably, there are none-or very few-in which case talk about evolution of the language capacity is beside the point. (Chomsky, 1972, p. 98)

    13) The Development of Language

   [It is] truth value rather than syntactic well-formedness that chiefly governs explicit verbal reinforcement by parents-which renders mildly paradoxical the fact that the usual product of such a training schedule is an adult whose speech is highly grammatical but not notably truthful. (R. O. Brown, 1973, p. 330)

    14) Sentential and Conceptual Levels in Language

   he conceptual base is responsible for formally representing the concepts underlying an utterance.... A given word in a language may or may not have one or more concepts underlying it.... On the sentential level, the utterances of a given language are encoded within a syntactic structure of that language. The basic construction of the sentential level is the sentence.

   The next highest level... is the conceptual level. We call the basic construction of this level the conceptualization. A conceptualization consists of concepts and certain relations among those concepts. We can consider that both levels exist at the same point in time and that for any unit on one level, some corresponding realizate exists on the other level. This realizate may be null or extremely complex.... Conceptualizations may relate to other conceptualizations by nesting or other specified relationships. (Schank, 1973, pp. 191-192)

    15) Linguistic Realities Have Not Yet Been Captured by Theoretical Models

   The mathematics of multi-dimensional interactive spaces and lattices, the projection of "computer behavior" on to possible models of cerebral functions, the theoretical and mechanical investigation of artificial intelligence, are producing a stream of sophisticated, often suggestive ideas.

   But it is, I believe, fair to say that nothing put forward until now in either theoretic design or mechanical mimicry comes even remotely in reach of the most rudimentary linguistic realities. (Steiner, 1975, p. 284)

    16) The Final Steps to Human Language

   The step from the simple tool to the master tool, a tool to make tools (what we would now call a machine tool), seems to me indeed to parallel the final step to human language, which I call reconstitution. It expresses in a practical and social context the same understanding of hierarchy, and shows the same analysis by function as a basis for synthesis. (Bronowski, 1977, pp. 127-128)

    17) The Inadequacy of Formal Linguistic Models for Ordinary Language Usage

    t is the language donn eґ in which we conduct our lives.... We have no other. And the danger is that formal linguistic models, in their loosely argued analogy with the axiomatic structure of the mathematical sciences, may block perception.... It is quite conceivable that, in language, continuous induction from simple, elemental units to more complex, realistic forms is not justified. The extent and formal "undecidability" of context-and every linguistic particle above the level of the phoneme is context-bound-may make it impossible, except in the most abstract, meta-linguistic sense, to pass from "pro-verbs," "kernals," or "deep deep structures" to actual speech. (Steiner, 1975, pp. 111-113)

    18) When a Language Is an Abstract Machine

   A higher-level formal language is an abstract machine. (Weizenbaum, 1976, p. 113)

    19) Metaphor and Metonymy Underpin the Formation of Linguistic Signs

   Jakobson sees metaphor and metonymy as the characteristic modes of binarily opposed polarities which between them underpin the two-fold process of selection and combination by which linguistic signs are formed.... Thus messages are constructed, as Saussure said, by a combination of a "horizontal" movement, which combines words together, and a "vertical" movement, which selects the particular words from the available inventory or "inner storehouse" of the language. The combinative (or syntagmatic) process manifests itself in contiguity (one word being placed next to another) and its mode is metonymic. The selective (or associative) process manifests itself in similarity (one word or concept being "like" another) and its mode is metaphoric. The "opposition" of metaphor and metonymy therefore may be said to represent in effect the essence of the total opposition between the synchronic mode of language (its immediate, coexistent, "vertical" relationships) and its diachronic mode (its sequential, successive, lineal progressive relationships). (Hawkes, 1977, pp. 77-78)

    20) Language and the Analysis of Nature

   It is striking that the layered structure that man has given to language constantly reappears in his analyses of nature. (Bronowski, 1977, p. 121)

    21) Correspondence Rules for Mapping Old Theory into Subsets of New Theory

   First, [an ideal intertheoretic reduction] provides us with a set of rules"correspondence rules" or "bridge laws," as the standard vernacular has it-which effect a mapping of the terms of the old theory (T o) onto a subset of the expressions of the new or reducing theory (T n). These rules guide the application of those selected expressions of T n in the following way: we are free to make singular applications of their correspondencerule doppelgangers in T o....

   Second, and equally important, a successful reduction ideally has the outcome that, under the term mapping effected by the correspondence rules, the central principles of T o (those of semantic and systematic importance) are mapped onto general sentences of T n that are theorems of Tn. (P. Churchland, 1979, p. 81)

    22) The Inclusion of Non- linguistic Factors in a Theory of Grammar

   If non-linguistic factors must be included in grammar: beliefs, attitudes, etc. [this would] amount to a rejection of the initial idealization of language as an object of study. A priori such a move cannot be ruled out, but it must be empirically motivated. If it proves to be correct, I would conclude that language is a chaos that is not worth studying.... Note that the question is not whether beliefs or attitudes, and so on, play a role in linguistic behavior and linguistic judgments... [but rather] whether distinct cognitive structures can be identified, which interact in the real use of language and linguistic judgments, the grammatical system being one of these. (Chomsky, 1979, pp. 140, 152-153)

    23) Language Is Inevitably Influenced by Specific Contexts of Human Interaction

   Language cannot be studied in isolation from the investigation of "rationality." It cannot afford to neglect our everyday assumptions concerning the total behavior of a reasonable person.... An integrational linguistics must recognize that human beings inhabit a communicational space which is not neatly compartmentalized into language and nonlanguage.... It renounces in advance the possibility of setting up systems of forms and meanings which will "account for" a central core of linguistic behavior irrespective of the situation and communicational purposes involved. (Harris, 1981, p. 165)

    24) The Genetic Blueprints of Language

   By innate [linguistic knowledge], Chomsky simply means "genetically programmed." He does not literally think that children are born with language in their heads ready to be spoken. He merely claims that a "blueprint is there, which is brought into use when the child reaches a certain point in her general development. With the help of this blueprint, she analyzes the language she hears around her more readily than she would if she were totally unprepared for the strange gabbling sounds which emerge from human mouths. (Aitchison, 1987, p. 31)

    25) Languages Are Machines

   Looking at ourselves from the computer viewpoint, we cannot avoid seeing that natural language is our most important "programming language." This means that a vast portion of our knowledge and activity is, for us, best communicated and understood in our natural language.... One could say that natural language was our first great original artifact and, since, as we increasingly realize, languages are machines, so natural language, with our brains to run it, was our primal invention of the universal computer. One could say this except for the sneaking suspicion that language isn't something we invented but something we became, not something we constructed but something in which we created, and recreated, ourselves. (Leiber, 1991, p. 8)

1) Military: System of systems

2) Engineering: core system

3) Telecommunications: platform

4) Information technology: basic system, kernel system

5) Programming: entry-level system (минимальная вычислительная система, ресурсы которой достаточны для использования серьезных прикладных программ типа текстовых процессоров, электронных таблиц и т.п.)

. в соединении с; совместно с

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Hydrazine hydrate can be used as a rocket fuel in association with nitric acid.

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Coupled (or In combination, or Together) with a recording system, these devices are used to measure...

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The system can be used in conjunction with a computer to perform diagnostic programming and checking industrial processes.

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A neoplasm can often be suspected on the basis of the findings from the history and the examination in conjunction with a routine blood count ( med).

•

When coupled with solubility information on common salts this will allow us to develop quite a variety of "predictable" processes.

* * *

 Some European incinerators use the rotary kiln in conjunction with a flowthrough furnace.

 These observations combined with the well-founded assumptions as to the basic nature of rotating stall have produced an excellent correlation.

 Hence the inlet conditions may be described as near uniform flow coupled with a high rate of mixing in the near wall regions.

 The instrument, together with the calibration adopted, enables the average temperature of the ring to be measured to an accuracy of + 1K.

* * *

агрегатнопото́чный ме́тод — conveyor-type production [production-line] method

аксиомати́ческий ме́тод — axiomatic [postulational] method

ме́тод амплиту́дного ана́лиза — kick-sorting method

анаглифи́ческий ме́тод картогр. — anaglyphic(al) method

ме́тод аналити́ческой вста́вки топ. — cantilever extension, cantilever (strip) triangulation

ме́тод быстре́йшего спу́ска стат. — steepest descent method

вариацио́нный ме́тод — variational method

ме́тод Верне́йля радио — Verneuil method

весово́й ме́тод — gravimetric method

ме́тод ветве́й и грани́ц киб. — branch and bound method

ме́тод взба́лтывания — shake method

визуа́льный ме́тод — visual method

ме́тод возду́шной прое́кции — aero-projection method

ме́тод враще́ния — method of revolution

ме́тод вреза́ния — plunge-cut method

ме́тод вре́мени пролё́та — time-of-flight method

вре́мя-и́мпульсный ме́тод ( преобразования аналоговой информации в дискретную) — pulse-counting method (of analog-to-digital conversion)

ме́тод встре́чного фрезерова́ния — conventional [cut-up] milling method

ме́тод вы́бега эл. — retardation method

ме́тод вымета́ния мат. — sweep(ing)-out method

ме́тод гармони́ческого бала́нса киб., автмт. — describing function method

ме́тод гармони́ческой линеариза́ции — describing function method

голографи́ческий ме́тод — holographic method

гравиметри́ческий ме́тод — gravimetric(al) method

графи́ческий ме́тод — graphical method

ме́тод графи́ческого трансформи́рования топ. — grid method

графоаналити́ческий ме́тод — semigraphical method

ме́тод гра́фов мат. — graph method

группово́й ме́тод ( в высокочастотной телефонии) — grouped-frequency basis

систе́ма рабо́тает групповы́м ме́тодом — the system operates on the grouped-frequency basis

ме́тод двух ре́ек геод., топ. — two-staff [two-base] method

ме́тод двух узло́в ( в анализе электрических цепей) — nodal-pair method

ме́тод дирекцио́нных угло́в геод. — method of gisements

ме́тод запа́са про́чности ( в расчетах конструкции) — load factor method

ме́тод засе́чек афс. — resection method

ме́тод зерка́льных изображе́ний эл. — method of electrical images

ме́тод зо́нной пла́вки ( в производстве монокристаллов полупроводниковых материалов) — floating-zone method, floating-zone technique

ме́тод избы́точных концентра́ций ( для опробования гипотетического механизма реакции) — isolation method (of the testing the rate equations)

ме́тод измере́ния, абсолю́тный — absolute [fundamental] method of measurement

ме́тод измере́ния, конта́ктный — contact method of measurement

ме́тод измере́ния, ко́свенный — indirect method of measurement

ме́тод измере́ния, относи́тельный — relative method of measurement

ме́тод измере́ния по то́чкам — point-by-point method

ме́тод измере́ния, прямо́й — direct method of measurement

ме́тод измере́ния угло́в по аэросни́мкам — photogoniometric method

ме́тод изображе́ний эл. — method of images, image method

ме́тод изото́пных индика́торов — tracer method

иммерсио́нный ме́тод — immersion method

и́мпульсный ме́тод свар. — pulse method

ме́тод и́мпульсов — momentum-transfer method

ме́тод инве́рсии — inversion method

и́ндексно-после́довательный ме́тод до́ступа, основно́й вчт. — basic indexed sequential access method, BISAM

и́ндексно-после́довательный ме́тод до́ступа с очередя́ми вчт. — queued indexed sequential access method, BISAM

интерференцио́нный ме́тод — interferometric method

ме́тод испыта́ний — testing procedure, testing method

ме́тод испыта́ний, кисло́тный — acid test

ме́тод испыта́ний, пане́льный — panel-spalling test

ме́тод испыта́тельной строки́ тлв. — test-line method

ме́тод иссле́дований напряже́ний, опти́ческий — optical stress analysis

ме́тод истече́ния — efflux method

ме́тод итера́ции — iteration method, iteration technique

ме́тод итера́ции приво́дит к сходи́мости проце́сса — the iteration (process) converges to a solution

ме́тод итера́ции приво́дит к (бы́строй или ме́дленной) сходи́мости проце́сса — the iteration (process) converges quickly or slowly

ме́тод картосоставле́ния — map-compilation [plotting] method

ме́тод кача́ющегося криста́лла ( в рентгеноструктурном анализе) — rotating-crystal method

ка́чественный ме́тод — qualitative method

кессо́нный ме́тод — caisson method

коли́чественный ме́тод — quantitative method

колориметри́ческий ме́тод — colorimetric method

ме́тод кольца́ и ша́ра — ball-and-ring method

комплексометри́ческий ме́тод ( для определения жёсткости воды) — complexometric method

кондуктометри́ческий ме́тод — conductance-measuring method

ме́тод коне́чных ра́зностей — finite difference method

ме́тод консерви́рования — curing method

ме́тод контро́ля, дифференци́рованный — differential control method

ме́тод контро́ля ка́чества — quality control method

ме́тод ко́нтурных то́ков — mesh-current [loop] method

ме́тод ко́нуса — cone method

ме́тод корнево́го годо́графа киб., автмт. — root-locus method

корреляцио́нный ме́тод — correlation method

ко́свенный ме́тод — indirect method

ме́тод кра́сок ( в дефектоскопии) — dye-penetrant method

лаборато́рный ме́тод — laboratory method

ме́тод ла́ковых покры́тий ( в сопротивлении материалов) — brittle-varnish method

ме́тод лине́йной интерполя́ции — method of proportional parts

ме́тод Ляпуно́ва аргд. — Lyapunov's method

ме́тод магни́тного порошка́ ( в дефектоскопии) — magnetic particle [magnetic powder] method

магни́тно-люминесце́нтный ме́тод ( в дефектоскопии) — fluorescent magnetic particle method

ме́тод ма́лого пара́метра киб., автмт. — perturbation theory, perturbation method

ме́тод ма́лых возмуще́ний аргд. — perturbation method

ме́тод мгнове́нной равносигна́льной зо́ны рлк. — simultaneous lobing [monopulse] method

ме́тод механи́ческой обрабо́тки — machining method

ме́тод ме́ченых а́томов — tracer method

ме́тод микрометри́рования — micrometer method

ме́тод мно́жителей Лагра́нжа — Lagrangian multiplier method, Lagrange's method of undetermined multipliers

ме́тод моме́нтных площаде́й мех. — area moment method

ме́тод Мо́нте-Ка́рло мат. — Monte Carlo method

ме́тод навига́ции, дальноме́рный ( пересечение двух окружностей) — rho-rho [r-r] navigation

ме́тод навига́ции, угломе́рный ( пересечение двух линий пеленга) — theta-theta [q-q] navigation

ме́тод наиме́ньших квадра́тов — method of least squares, least-squares technique

ме́тод наискоре́йшего спу́ска мат. — method of steepest descent

ме́тод нака́чки ( лазера) — pumping [excitation] method

ме́тод накопле́ния яд. физ. — “backing-space” method

ме́тод наложе́ния — method of superposition

ме́тод напыле́ния — evaporation technique

ме́тод нару́жных заря́дов горн. — adobe blasting method

ме́тод незави́симых стереопа́р топ. — method of independent image pairs

ненулево́й ме́тод — deflection method

ме́тод неопределё́нных мно́жителей Лагра́нжа — Lagrangian multiplier method, Lagrange's method of undetermined multipliers

ме́тод неподви́жных то́чек — method of fixed points

неразруша́ющий ме́тод — non-destructive method, non-destructive testing

нерекурси́вный ме́тод — non-recursive method

нето́чный ме́тод — inexact method

нефелометри́ческий ме́тод — nephelometric method

ме́тод нивели́рования по частя́м — method of fraction levelling

нулево́й ме́тод — null [zero(-deflection) ] method

ме́тод нулевы́х бие́ний — zero-beat method

ме́тод нулевы́х то́чек — neutral-points method

ме́тод обеспе́чения надё́жности — reliability method

ме́тод обрабо́тки — processing [working, tooling] method

ме́тод обра́тной простра́нственной засе́чки топ. — method of pyramid

обра́тно-ступе́нчатый ме́тод свар. — step-back method

ме́тод объединё́нного а́тома — associate atom method

объекти́вный ме́тод — objective method

объё́мный ме́тод — volumetric method

ме́тод одного́ отсчё́та ( преобразование непрерывной информации в дискретную) — the total value method (of analog-to-digital conversion)

окисли́тельно-восстанови́тельный ме́тод — redox method

опера́торный ме́тод — operational method

ме́тод определе́ния ме́ста, дальноме́рно-пеленгацио́нный ( пересечение прямой и окружности) — rho-theta [r-q] fixing

ме́тод определе́ния ме́ста, дальноме́рный ( пересечение двух окружностей) — rho-rho [r-r] fixing

ме́тод определе́ния ме́ста, пеленгацио́нный ( пересечение двух линий пеленга) — theta-theta [q-q] fixing

ме́тод определе́ния отбе́ливаемости и цве́тности ма́сел — bleach-and-colour method

ме́тод определе́ния положе́ния ли́нии, двукра́тный геод. — double-line method

ме́тод опти́ческой корреля́ции — optical correlation technique

ме́тод осажде́ния — sedimentation method

ме́тод осо́бых возмуще́ний аргд. — singular perturbation method

ме́тод осредне́ния — averaging [smoothing] method

ме́тод отбо́ра проб — sampling method, sampling technique

ме́тод отклоне́ния — deflection method

ме́тод отопле́ния метал. — fuel practice

ме́тод отраже́ния — reflection method

ме́тод отражё́нных и́мпульсов — pulse-echo method

ме́тод отыска́ния произво́дной, непосре́дственный — delta method

ме́тод па́дающего те́ла — falling body method

ме́тод парамагни́тного резона́нса — paramagnetic-resonance method

ме́тод пе́рвого приближе́ния — first approximation method

ме́тод перева́ла мат. — saddle-point method

ме́тод перено́са коли́чества движе́ния аргд. — momentum-transfer method

ме́тод перераспределе́ния моме́нтов ( в расчёте конструкций) — moment distribution method

ме́тод пересека́ющихся луче́й — crossed beam method

ме́тод перехо́дного состоя́ния ( в аналитической химии) — transition state method

ме́тод перпендикуля́ров — offset method

ме́тод перспекти́вных се́ток топ. — grid method

ме́тод пескова́ния с.-х. — sanding method

пикнометри́ческий ме́тод — bottle method

ме́тод площаде́й физ. — area method

ме́тод повторе́ний геод. — method of reiteration, repetition method

ме́тод подбо́ра — trial-and-error [cut-and-try] method

ме́тод подо́бия — similitude method

ме́тод подориенти́рования топ. — setting on points of control

ме́тод по́лной деформа́ции — total-strain method

ме́тод полови́нных отклоне́ний — half-deflection method

ме́тод положе́ния геод. — method of bearings, method of gisements

полуколи́чественный ме́тод — semiquantitative method

ме́тод поля́рных координа́т — polar method

ме́тод попу́тного фрезерова́ния — climb [cut-down] milling method

порошко́вый ме́тод ( в рентгеноструктурном анализе) — powder [Debye-Scherer-Hull] method

ме́тод посе́ва — seeding technique

ме́тод после́довательного счё́та ( преобразования аналоговой информации в дискретную) — incremental method (of analog-to-digital conversion)

ме́тод после́довательных исключе́ний — successive exclusion method

ме́тод после́довательных подстано́вок — method of successive substitution, substitution process

ме́тод после́довательных попра́вок — successive correction method

ме́тод после́довательных приближе́ний — successive approximation method

ме́тод после́довательных элимина́ций — method of exhaustion

ме́тод послесплавно́й диффу́зии полупр. — post-alloy-diffusion technique

потенциометри́ческий компенсацио́нный ме́тод — potentiometric method

пото́чно-конве́йерный ме́тод — flow-line conveyor method

пото́чный ме́тод — straight-line flow method

ме́тод прерыва́ний ( для измерения скорости света) — chopped-beam method

приближё́нный ме́тод — approximate method

ме́тод проб и оши́бок — trial-and-error [cut-and-try] method

ме́тод программи́рующих програ́мм — programming program method

ме́тод продолже́ния топ. — setting on points on control

ме́тод проекти́рования, моде́льно-маке́тный — model-and-mock-up method of design

ме́тод простра́нственного коди́рования ( преобразования аналоговой информации в дискретную) — coded pattern method (OF analog-to-digital conversion)

ме́тод простра́нственной самофикса́ции — self-fixation space method

прямо́й ме́тод — direct method

ме́тод псевдослуча́йных чи́сел — pseudorandom number method

ме́тод равносигна́льной зо́ны рлк. — lobing, beam [lobe] switching

ме́тод равносигна́льной зо́ны, мгнове́нный рлк. — simultaneous lobing, monopulse

ме́тод ра́вных высо́т геод. — equal-altitude method

ме́тод ра́вных деформа́ций ( в проектировании бетонных конструкций) — equal-strain method

ме́тод ра́вных отклоне́ний — equal-deflection method

радиацио́нный ме́тод — radiation method

ме́тод радиоавтогра́фии — radioautograph technique

ме́тод радиоакти́вных индика́торов — tracer method

радиометри́ческий ме́тод — radiometric method

ме́тод разбавле́ния — dilution method

ме́тод разделе́ния тлв. — separation method

ме́тод разделе́ния переме́нных — method of separation of variables

ме́тод разли́вки метал. — teeming [pouring, casting] practice

ме́тод разме́рностей — dimensional method

ра́зностный ме́тод — difference method

ме́тод разруша́ющей нагру́зки — load-factor method

разруша́ющий ме́тод — destructive check

ме́тод рассе́яния Рэле́я — Rayleigh scattering method

ме́тод ра́стра тлв. — grid method

ме́тод ра́стрового скани́рования — raster-scan method

ме́тод расчё́та по допусти́мым нагру́зкам — working stress design [WSD] method

ме́тод расчё́та по разруша́ющим нагру́зкам стр. — ultimate-strength design [USD] method

ме́тод расчё́та при по́мощи про́бной нагру́зки стр. — trial-load method

ме́тод расчё́та, упру́гий стр. — elastic method

резона́нсный ме́тод — resonance method

ме́тод реитера́ций геод. — method of reiteration, repetition method

рентгенострукту́рный ме́тод — X-ray diffraction method

ме́тод реше́ния зада́чи о четвё́ртой то́чке геод. — three-point method

ме́тод решета́ мат. — sieve method

ру́порно-ли́нзовый ме́тод радио — horn-and-lens method

ме́тод самоторможе́ния — retardation method

ме́тод сви́лей — schlieren technique, schlieren method

ме́тод сдви́нутого сигна́ла — offset-signal method

ме́тод секу́щих — secant method

ме́тод се́рого кли́на физ. — gray-wedge method

ме́тод се́ток мат., вчт. — net(-point) method

ме́тод сече́ний ( в расчёте напряжений в фермах) — method of sections

ме́тод сил ( определение усилий в статически неопределимой системе) — work method

символи́ческий ме́тод — method of complex numbers

ме́тод симметри́чных составля́ющих — method of symmetrical components, symmetrical component method

ме́тод синхро́нного накопле́ния — synchronous storage method

ме́тод скани́рования полосо́й — single-line-scan television method

ме́тод скани́рования пятно́м — spot-scan photomultiplier method

ме́тод смеще́ния отде́льных узло́в стр. — method of separate joint displacement

ме́тод совпаде́ний — coincidence method

ме́тод сосредото́ченных пара́метров — lumped-parameter method

ме́тод спада́ния заря́да — fall-of-charge method

спектроскопи́ческий ме́тод — spectroscopic method

ме́тод спира́льного скани́рования — spiral-scan method

ме́тод сплавле́ния — fusion method

ме́тод сплошны́х сред ( в моделировании) — continuous field analog technique

ме́тод сре́дних квадра́тов — midsquare method

статисти́ческий ме́тод — statistical technique

статисти́ческий ме́тод оце́нки — statistical estimation

ме́тод статисти́ческих испыта́ний — Monte Carlo method

стробоголографи́ческий ме́тод — strobo-holographic method

стробоскопи́ческий ме́тод — stroboscopic method

стру́йный ме́тод метал. — jet test

ступе́нчатый ме́тод ( сварки или сверления) — step-by-step method

субъекти́вный ме́тод — subjective method

ме́тод сухо́го озоле́ния — dry combustion method

ме́тод сухо́го порошка́ ( в дефектоскопии) — dry method

счё́тно-и́мпульсный ме́тод — pulse-counting method

табли́чный ме́тод — diagram method

телевизио́нный ме́тод электро́нной аэросъё́мки — television method

телевизио́нный ме́тод электро́нной фотограмме́трии — television method

тенево́й ме́тод — (direct-)shadow method

термоанемометри́ческий ме́тод — hot-wire method

топологи́ческий ме́тод — topological method

ме́тод то́чечного вплавле́ния полупр. — dot alloying method

то́чный ме́тод — exact [precision] method

ме́тод травле́ния, гидри́дный — sodium hydride descaling

ме́тод трапецеида́льных характери́стик — Floyd's trapezoidal approximation method, approximation procedure

ме́тод трёх баз геод. — three-base method

ме́тод триангуля́ции — triangulation method

ме́тод трилатера́ции геод. — trilateration method

ме́тод углово́й деформа́ции — slope-deflection method

ме́тод углово́й модуля́ции — angular modulation method

ме́тод удаля́емого трафаре́та полупр. — rejection mask method

ме́тод удаля́емой ма́ски рад. — rejection mask method

ме́тод узло́в ( в расчёте напряжении в фермах) — method of joints

ме́тод узловы́х потенциа́лов — node-voltage method

ме́тод ура́внивания по направле́ниям геод. — method of directions, direction method

ме́тод ура́внивания по угла́м геод. — method of angles, angle method

ме́тод уравнове́шивания — balancing method

ме́тод усредне́ния — averaging [smoothing] method

ме́тод фа́зового контра́ста ( в микроскопии) — phase contrast

наблюда́ть ме́тодом фа́зового контра́ста — examine [study] by phase contrast

ме́тод фа́зовой пло́скости — phase plane method

ме́тод факториза́ции — factorization method

флотацио́нный ме́тод — floatation method

ме́тод формирова́ния сигна́лов цве́тности тлв. — colour-processing method

ме́тод центрифуги́рования — centrifuge method

цепно́й ме́тод астр. — chain method

чи́сленный ме́тод — numerical method

ме́тод Чохра́льского ( в выращивании полупроводниковых кристаллов) — Czochralski method, vertical pulling technique

ме́тод Шо́ра — Shore hardness

щупово́й ме́тод — stylus method

ме́тод электрофоре́за — electrophoretic method

эмпири́ческий ме́тод — trial-and-error [cut-and-try] method

энергети́ческий ме́тод

1. косм. energy method

2. стр. strain energy method

ме́тод энергети́ческого бала́нса — power balance method

эргати́ческий ме́тод ( при общении человека с ЭВМ) — interactive [conversational] technique

 

программируемый логический контроллер
ПЛК
-
[Интент]

контроллер
Управляющее устройство, осуществляющее автоматическое управление посредством программной реализации алгоритмов управления.
[Сборник рекомендуемых терминов. Выпуск 107. Теория управления.
 Академия наук СССР. Комитет научно-технической терминологии. 1984 г.]

EN

storage-programmable logic controller
computer-aided control equipment or system whose logic sequence can be varied via a directly or remote-control connected programming device, for example a control panel, a host computer or a portable terminal
[IEV ref 351-32-34]

FR

automate programmable à mémoire
équipement ou système de commande assisté par ordinateur dont la séquence logique peut être modifiée directement ou par l'intermédiaire d'un dispositif de programmation relié à une télécommande, par exemple un panneau de commande, un ordinateur hôte ou un terminal de données portatif
[IEV ref 351-32-34]

  См. также:
- архитектура контроллера;
- производительность контроллера;
- время реакции контроллера;
КЛАССИФИКАЦИЯ
  Основным показателем ПЛК является количество каналов ввода-вывода. По этому признаку ПЛК делятся на следующие группы:

• нано- ПЛК (менее 16 каналов);
• микро-ПЛК (более 16, до 100 каналов);
• средние (более 100, до 500 каналов);
• большие (более 500 каналов).

По расположению модулей ввода-вывода ПЛК бывают:

• моноблочными - в которых устройство ввода-вывода не может быть удалено из контроллера или заменено на другое. Конструктивно контроллер представляет собой единое целое с устройствами ввода-вывода (например, одноплатный контроллер). Моноблочный контроллер может иметь, например, 16 каналов дискретного ввода и 8 каналов релейного вывода;
• модульные - состоящие из общей корзины (шасси), в которой располагаются модуль центрального процессора и сменные модули ввода-вывода. Состав модулей выбирается пользователем в зависимости от решаемой задачи. Типовое количество слотов для сменных модулей - от 8 до 32;
• распределенные (с удаленными модулями ввода-вывода) - в которых модули ввода-вывода выполнены в отдельных корпусах, соединяются с модулем контроллера по сети (обычно на основе интерфейса RS-485) и могут быть расположены на расстоянии до 1,2 км от процессорного модуля.

Часто перечисленные конструктивные типы контроллеров комбинируются, например, моноблочный контроллер может иметь несколько съемных плат; моноблочный и модульный контроллеры могут быть дополнены удаленными модулями ввода-вывода, чтобы увеличить общее количество каналов.

Многие контроллеры имеют набор сменных процессорных плат разной производительности. Это позволяет расширить круг потенциальных пользователей системы без изменения ее конструктива.

По конструктивному исполнению и способу крепления контроллеры делятся на:

• панельные (для монтажа на панель или дверцу шкафа);
• для монтажа на DIN-рейку внутри шкафа;
• для крепления на стене;
• стоечные - для монтажа в стойке;
• бескорпусные (обычно одноплатные) для применения в специализированных конструктивах производителей оборудования (OEM - "Original Equipment Manufact urer").

По области применения контроллеры делятся на следующие типы:

• универсальные общепромышленные;
• для управления роботами;
• для управления позиционированием и перемещением;
• коммуникационные;
• ПИД-контроллеры;
• специализированные.

По способу программирования контроллеры бывают:

• программируемые с лицевой панели контроллера;
• программируемые переносным программатором;
• программируемые с помощью дисплея, мыши и клавиатуры;
• программируемые с помощью персонального компьютера.

Контроллеры могут программироваться на следующих языках:

• на классических алгоритмических языках (C, С#, Visual Basic);
• на языках МЭК 61131-3.

Контроллеры могут содержать в своем составе модули ввода-вывода или не содержать их. Примерами контроллеров без модулей ввода-вывода являются коммуникационные контроллеры, которые выполняют функцию межсетевого шлюза, или контроллеры, получающие данные от контроллеров нижнего уровня иерархии АСУ ТП.   Контроллеры для систем автоматизации

Слово "контроллер" произошло от английского "control" (управление), а не от русского "контроль" (учет, проверка). Контроллером в системах автоматизации называют устройство, выполняющее управление физическими процессами по записанному в него алгоритму, с использованием информации, получаемой от датчиков и выводимой в исполнительные устройства.

Первые контроллеры появились на рубеже 60-х и 70-х годов в автомобильной промышленности, где использовались для автоматизации сборочных линий. В то время компьютеры стоили чрезвычайно дорого, поэтому контроллеры строились на жесткой логике (программировались аппаратно), что было гораздо дешевле. Однако перенастройка с одной технологической линии на другую требовала фактически изготовления нового контроллера. Поэтому появились контроллеры, алгоритм работы которых мог быть изменен несколько проще - с помощью схемы соединений реле. Такие контроллеры получили название программируемых логических контроллеров (ПЛК), и этот термин сохранился до настоящего времени. Везде ниже термины "контроллер" и "ПЛК" мы будем употреблять как синонимы.

Немного позже появились ПЛК, которые можно было программировать на машинно-ориентированном языке, что было проще конструктивно, но требовало участия специально обученного программиста для внесения даже незначительных изменений в алгоритм управления. С этого момента началась борьба за упрощение процесса программирования ПЛК, которая привела сначала к созданию языков высокого уровня, затем - специализированных языков визуального программирования, похожих на язык релейной логики. В настоящее время этот процесс завершился созданием международного стандарта IEC (МЭК) 1131-3, который позже был переименован в МЭК 61131-3. Стандарт МЭК 61131-3 поддерживает пять языков технологического программирования, что исключает необходимость привлечения профессиональных программистов при построении систем с контроллерами, оставляя для них решение нестандартных задач.

В связи с тем, что способ программирования является наиболее существенным классифицирующим признаком контроллера, понятие "ПЛК" все реже используется для обозначения управляющих контроллеров, которые не поддерживают технологические языки программирования.   Жесткие ограничения на стоимость и огромное разнообразие целей автоматизации привели к невозможности создания универсального ПЛК, как это случилось с офисными компьютерами. Область автоматизации выдвигает множество задач, в соответствии с которыми развивается и рынок, содержащий сотни непохожих друг на друга контроллеров, различающихся десятками параметров.

Выбор оптимального для конкретной задачи контроллера основывается обычно на соответствии функциональных характеристик контроллера решаемой задаче при условии минимальной его стоимости. Учитываются также другие важные характеристики (температурный диапазон, надежность, бренд изготовителя, наличие разрешений Ростехнадзора, сертификатов и т. п.).

Несмотря на огромное разнообразие контроллеров, в их развитии заметны следующие общие тенденции:

• уменьшение габаритов;
• расширение функциональных возможностей;
• увеличение количества поддерживаемых интерфейсов и сетей;
• использование идеологии "открытых систем";
• использование языков программирования стандарта МЭК 61131-3;
• снижение цены.

Еще одной тенденцией является появление в контроллерах признаков компьютера (наличие мыши, клавиатуры, монитора, ОС Windows, возможности подключения жесткого диска), а в компьютерах - признаков контроллера (расширенный температурный диапазон, электронный диск, защита от пыли и влаги, крепление на DIN-рейку, наличие сторожевого таймера, увеличенное количество коммуникационных портов, использование ОС жесткого реального времени, функции самотестирования и диагностики, контроль целостности прикладной программы). Появились компьютеры в конструктивах для жестких условий эксплуатации. Аппаратные различия между компьютером и контроллером постепенно исчезают. Основными отличительными признаками контроллера остаются его назначение и наличие технологического языка программирования.

[ http://bookasutp.ru/Chapter6_1.aspx]  

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Программируемый логический контроллер (ПЛК, PLC) – микропроцессорное устройство, предназначенное для управления технологическим процессом и другими сложными технологическими объектами.
Принцип работы контроллера состоит в выполнение следующего цикла операций:

1.    Сбор сигналов с датчиков;
2.    Обработка сигналов согласно прикладному алгоритму управления;
3.    Выдача управляющих воздействий на исполнительные устройства.

В нормальном режиме работы контроллер непрерывно выполняет этот цикл с частотой от 50 раз в секунду. Время, затрачиваемое контроллером на выполнение полного цикла, часто называют временем (или периодом) сканирования; в большинстве современных ПЛК сканирование может настраиваться пользователем в диапазоне от 20 до 30000 миллисекунд. Для быстрых технологических процессов, где критична скорость реакции системы и требуется оперативное регулирование, время сканирования может составлять 20 мс, однако для большинства непрерывных процессов период 100 мс считается вполне приемлемым.

Аппаратно контроллеры имеют модульную архитектуру и могут состоять из следующих компонентов:

1.    Базовая панель ( Baseplate). Она служит для размещения на ней других модулей системы, устанавливаемых в специально отведенные позиции (слоты). Внутри базовой панели проходят две шины: одна - для подачи питания на электронные модули, другая – для пересылки данных и информационного обмена между модулями.

2.    Модуль центрального вычислительного устройства ( СPU). Это мозг системы. Собственно в нем и происходит математическая обработка данных. Для связи с другими устройствами CPU часто оснащается сетевым интерфейсом, поддерживающим тот или иной коммуникационный стандарт.

3.    Дополнительные коммуникационные модули. Необходимы для добавления сетевых интерфейсов, неподдерживаемых напрямую самим CPU. Коммуникационные модули существенно расширяют возможности ПЛК по сетевому взаимодействию. C их помощью к контроллеру подключают узлы распределенного ввода/вывода, интеллектуальные полевые приборы и станции операторского уровня.

4.    Блок питания. Нужен для запитки системы от 220 V. Однако многие ПЛК не имеют стандартного блока питания и запитываются от внешнего.  

² = complete, full [fuller -comp., fullest -sup.], thorough, total, end to end, supine, unrelieved, utter, gavel to gavel, systemic, overarching, ultimate, avowed, out-and-out, certified, unmitigaged, fully blown, unreserved.

Ex. The main entry is the complete catalogue record of the document.

Ex. Since recall goes up as precision goes down, it is clearly not possible to achieve in general a system which gives full recall at the same time as full precision.

Ex. Timely and thorough planning is essential.

Ex. This situation requires a very skilled information worker if total disaster is to be avoided.

Ex. Next morning the heap, now damp right through, was set up on one end of the horse (later called the bank), a bench long enough to take two piles of paper end to end, and about as high as the coffin of the press.

Ex. 'I was saying that we shouldn't have a supine acceptance for temporary limitations'.

Ex. Although the slave narratives were usually intended to serve in the cause of abolition, not all of them were bitter, unrelieved tirades against the institution of slavery, but rather there were frequently moments of relieving laughter.

Ex. There is little to be said for this grudging acceptance or utter rejection of pseudonyms.

Ex. A survey of state legislators finds that lawmakers support expanding television coverage of legislative proceedings to include gavel to gavel programming.

Ex. There is a need for an examination of the whole process of information dissemination from a 'systemic' framework.

Ex. There appears to be an unhealthy tendency among information technology professionals to elevate any single, highly successful practical experience instantly into an overarching paradigm for managerial success.

Ex. The whole project is undeniably full of sentimental, cinephiliac rapture, but it provided the ultimate opportunity for filmmakers to talk feverishly about the basic nature of their medium.

Ex. Anne Bogart's novel combines avowed misogyny with postfeminist frolic.

Ex. Such an appraoch is unlikely to improve the social sciences unless valid informaton can first be distinguished from out-and-out incorrect information.

Ex. She is a certified TV-addict -- you simply cannot talk to her when she's glued to the box.

Ex. Only Bush could take a horrible situation and create an unmitigated disaster.

Ex. This time it's a hairline fracture rather than a fully blown break of a metatarsal, however the result is the same.

Ex. It is also important that we all give them our unreserved support.

----

* de movimiento total = full-motion.

* en total = all told, altogether, in all, overall, in total, in toto.

* fracaso total = complete failure.

* integración total = seamlessness.

* la suma total de = the total sum of, the sum total of.

* limpieza total = clean sweep.

* Número + en total = Número + in number.

* oscuridad total = pitch blackness, pitch darkness.

* rechazo total = bold statement against.

* síndrome de alergia total = total allergy syndrome.

* siniestro total = write-off [writeoff].

* suma total = sum total, count.

* total atención = undivided attention.

1 total (completo) (cifra, coste).

2 fab (informal) (fantastic).

basically, in a word.

total que me marché so anyway, I left

total, ¿qué más da? what difference does it make anyway?

in short.

Total,nadie acudió a su trabajo! In short, nobody came to work!

1 total (suma).

me da un total de 580 libras I make it »580

2 whole (totalidad, conjunto).

el total del grupo the whole group

nos costó 200 dólares en total it cost us 200 dollars in total o all

en total fuimos más de treinta personas in total there were more than thirty of us

* * *

► adjetivo

1 total, complete, overall

■ la imprenta supuso una revolución total printing brought about a complete revolution

■ anestesia total general anaesthetic

► nombre masculino

1 (totalidad) whole

■ el total de la población the whole population

2 (suma) total, sum

► adverbio

1 (en conclusión) in short, so

■ total, fue un fracaso in short, it was a failure

■ total, que se fueron porque quisieron they left because they wanted to

2 (al fin y al cabo) after all

■ total, para lo que me sirve... after all, for all the good it is to me...

\

en total in all

* * *

* * *

1. ADJ

1) (=absoluto) [éxito, fracaso] total

2) (=global) [importe, suma] total

3) * (=excelente) smashing, brilliant

2. ADV

1) (=resumiendo) in short, all in all; (=así que) so

2) (=al fin y al cabo) at the end of the day

SM (=suma total) total; (=totalidad) whole

* * *

a) ( absoluto) <desastre/destrucción> total; < éxito> resounding, total

b) ( global) <costo/importe> total

masculino total

adverbio (indep) (fam)

a) ( al resumir una narración) so, in the end

b) (expresando indiferencia, poca importancia)

* * *

a) ( absoluto) <desastre/destrucción> total; < éxito> resounding, total

b) ( global) <costo/importe> total

masculino total

adverbio (indep) (fam)

a) ( al resumir una narración) so, in the end

b) (expresando indiferencia, poca importancia)

* * *

total¹

¹ = tally [tallies, pl.], total, count, grand total.

total²

² = complete, full [fuller -comp., fullest -sup.], thorough, total, end to end, supine, unrelieved, utter, gavel to gavel, systemic, overarching, ultimate, avowed, out-and-out, certified, unmitigaged, fully blown, unreserved.

* * *

1 (absoluto) ‹desastre/destrucción› total; ‹éxito› resounding ( before n), total

la película fue un fracaso total the film was a total o an utter failure

un cambio total a complete change

2 (global) ‹coste/importe› total

total

¿cuánto es el total? what's the total?, what does it all come to?, how much is it altogether?

el total de las pérdidas/ganancias the total losses/profits

el total asciende a $40.000 the total amounts to o comes to o is $40,000

afecta a un total de 600 personas it affects a total of 600 people

en total altogether

son 5 euros en total that's 5 euros altogether

( indep) ( fam)

1 (al resumir una narración) so, in the end

total, que me di por vencida so in the end I gave up

(expresando indiferencia, poca importancia): ¿por qué no te quedas? total, mañana no tienes que trabajar why not stay? I mean o after all, you don't have to go to work tomorrow

* * *

a) ( absoluto) ‹desastre/destrucción› total;

b) ( global) ‹costo/importe› total

◊ en total altogether

* * *

♦ adj

1. [cifra, coste, gasto] total;

el importe total de las inversiones the total amount of the investments

2. [confianza, rechazo, ruptura] total, complete;

actúa con total libertad she acts completely freely, she has complete freedom of action;

su influencia en ellos es total he has overwhelming influence over them

3. Fam [fantástico] fab, Br brill

♦ nm

1. [suma] total;

el total de visitantes del museo alcanzó los tres millones the total number of visitors to the museum reached three million;

me da un total de 580 I make it 580

total de ventas total sales

2. [totalidad, conjunto] whole;

el total del grupo the whole group;

en total in total, in all;

nos costó 200 dólares en total it cost us 200 dollars in total o all;

en total fuimos más de treinta personas in total there were more than thirty of us

♦ adv

1. [en resumen] basically, in a word;

total, que me marché so anyway, I left;

total, que te has quedado sin trabajo, ¿no? basically, you're out of a job, then?

2. [en realidad] anyway;

total, ¿qué más da? what difference does it make anyway?;

llévatelo, total ¿para qué lo quiero yo? take it, what good is it to me, after all?

* * *

I adj total, complete;

en total altogether, in total

II m total;

un total de 50 personas a total of 50 people

III adv

total, que no conseguí estudiar the upshot was that I didn’t manage to get any studying done

* * *

total adv

: in the end, so

total, que no fui: in short, I didn't go

total adj & nm

: total

♦ totalmente adv

* * *

total¹ adj total / complete

total² adv so

total³ n total