Showing papers on "Fuzzy control system published in 1979"

Fuzzy logic and fuzzy reasoning

Abstract: The concepts of truth value restriction and fuzzy logical relation are used to give a general approach to fuzzy logic and also fuzzy reasoning involving propositions with imprecise or vague description.

Do we need “fuzzy logic”?

Abstract: This paper gives a critical appraisal of “fuzzy logic” from the viewpoint of a logician and concludes that no acceptable case has been made for the need for it

Fault isolation algorithm for analog electronic systems using the fuzzy concept

Abstract: We are mainly concerned with enhancing ATPG for analog nonlinear circuits. For simplicity we are dealing only with the isolation of single fault cases. Due to the imprecision and indeterminacy of the complex structure of faulty networks, it is usually difficult to obtain exact solutions. Furthermore, for fault isolation it is often unnecessary to seek the exact solutions. In fact we find it useful to treat such faulty networks as fuzzy systems. The algorithm presented herein makes use of the available measured data on port responses to isolate the faulty components based on fuzzy set concepts. An illustrative example using the NAP2 network analysis program is included. These results aie compared with previous results based on other criteria.

The State Space Approach

Abstract: The purpose of this chapter is to illustrate the procedure used for deriving the state representation of some typical production processes. The practitioner must master this very important step before he can try to design or modify the behaviour of a production process. The state of a system is defined as the minimum amount of information required to describe the condition of a system at any given time in such a way that, if the system input is known from that time on, and if the dynamics function governing the behaviour of the system is also known, the condition of the system at any future time is completely determined. We make explicit what we mean by continuous-time, discrete-time, linear and nonlinear systems. Further, we stress that there may be systems in which the current state and incoming inputs do not determine the future state precisely. In this book we shall emphasize the class of fuzzy systems considering the dynamics function as a fuzzy relation. Hopefully, this chapter, coupled with the reader’s own study of such topics as production processes and classical planning theory, will make it clear that the dynamic systems theory which we develop in the ensuing chapters is applicable to a wide variety of managerial situations.

Fuzzy Theory and Environmental Control in Buildings

Abstract: Current models of the environmental performance of buildings embody physical variables and are either deterministic or probabilistic or a combination of the two It is argued that this is an inappropriate basis for any submodel of occupant action to control the environment Fuzzy variables and fuzzy algorithms reflect the imprecision and complexity of the control exercised by people and have been used to model human control of industrial processes It is proposed that fuzzy theory be applied to the modelling of environmental control by building occupants A brief tutorial on fuzzy reasoning and its industrial applications is given and a research programme to establish a fuzzy model of environmental control is discussed

Analysis of closed loop fuzzy systems

Abstract: This paper is concerned with the analysis of closed loop systems in which the state and input variables are finite, discrete multi-dimensional fuzzy sets. Some results pertaining to the asymptotic behaviour of such systems are presented. A small class of feedback control problems is considered and some solutions discussed.