Showing papers on "Fuzzy control system published in 1976"

Foundations of fuzzy reasoning

Abstract: This paper gives an overview of the theory of fuzzy sets and fuzzy reasoning as proposed and developed by Lotfi Zadeh. In particular it reviews the philosophical and logical antecedents and foundations for this theory and its applications. The problem of borderline cases in set theory and the two classical approaches of precisifying them out, or admitting them as a third case, are discussed, leading to Zadeh's suggestion of continuous degrees of set membership. The extension of basic set operations to such fuzzy sets, and the relationship to other multivalued logics for set theory, are then outlined. The fuzzification of mathematical structures leads naturally to the concepts of fuzzy logics and inference, and consideration of implication suggests Łukasiewicz infinite-valued logic as a base logic for fuzzy reasoning. The paradoxes of the barber, and of sorites, are then analysed to illustrate fuzzy reasoning in action and lead naturally to Zadeh's theory of linguistic hedges and truth. Finally, the logical, modeltheoretic and psychological derivations of numeric values in fuzzy reasoning are discussed, and the rationale behind interest in fuzzy reasoning is summarized.

Fuzzy sets for man-machine interaction

Abstract: A new type of experiment is'proposed to better understand the fuzzy behaviour of a human operator in a man-machine system. The published applications of fuzzy set theory to the control of a simple steam engine are used as a convenient example to illustrate how some of the current applications of fuzzy set theory may be modified to carry out this type of experiment. The rationale for this proposal is developed by reviewing studies of the classification of human height and applications of fuzzy set theory to handwritten character recognition and control system design. Based on this brief review, both the results to be expected from such an experiment and how they might be analyzed are discussed. A key result is that such experiments ought to provide a much better understanding of the operator's fuzzy algorithm for adapting his experience to the development of the fuzzy algorithm for the new task.

Analysis of fuzzy control algorithms using the relation matrix

Abstract: This paper uses the relation matrix to examine the structure of fuzzy control algorithms. After introducing some basic notations and definitions, it presents a theorem which allows an arbitrary relation matrix to be translated into a set of fuzzy control rules. Using this result it is possible to show that the implementation of the algorithm does not affect its structure and that the most meaningful way of altering its performance is to change the rules themselves.

The implementation of fuzzy algorithms for control

Abstract: This letter describes the implementation of control systems designed using fuzzy algorithms and fuzzy logic. The resulting technique employs lookup tables. An assessment is made of the suitability of such tables, particularly when applied to short-word-length digital control systems. An interpreter program which can be used to generate the required lookup tables is also described.

Fuzzy robot controls

Abstract: A fuzzy program is defined as an ordered sequence of fuzzy instructions. In the execution of a fuzzy program, fuzzy instructions are translated into machine instructions by the use of MAX-METHOD and backtracking. To show how a fuzzy program is executed, a simulation system is exploited which controls a simple inchworm robot. A few examples of computer simulations are presented which deal with the behavior of a stranger (or a robot) searching for his destination in a modeled town under simple fuzzy instructions.

Fuzzy Models for Social Processes

Abstract: A general account of some techniques applied in the study of complex systems is given, suggesting their possible extensions in the field of social sciences. The theory of fuzzy sets is introduced as well-suited for modelling the social group. Fuzzy clustering, fuzzy categories and fuzzy systems are presented as possible models of social phenomena.