A new methodology of fuzzy constraint-based controller design via constraint-network processing

A complete design framework for a fuzzy constraint-based controller based on fuzzy constraint processing and its semantics and relationship to fuzzy logic is presented. Although, to date, many fuzzy logic control systems have been implemented in rule-based languages, we expect that eventually these languages will be supplanted by constraint-based languages. Despite the successes which have owed from the applications of rule-based fuzzy logic control systems, this paradigm ooers only a small part of the expressive competence of the rst-order predicate calculus. In addition, because constraints represent the requirements that the artifact being designed must satisfy, the design can be viewed as exploring alternatives in a solution space bounded by these constraints. In consequence , constraints are suitable to the task of mod-eling the controller in a dynamic control system so that the output is governed to a desired state as spec-iied by the constraints. In this paper, the concept of \fuzzy constraints" in a problem solving is introduced and some basic deenitions of fuzzy constraint processing in a constraint network and its semantic modeling are addressed. Then a fuzzy local propagation inference mechanism for reasoning about imprecise information applying the lter operation in a network of constraints is proposed. Moreover, we advance the concurrent fuzzy logic controller (FLC) to a new type of controller, the fuzzy constraint-based controller (FCC), using a more general predicate calculus and full rst-order logic knowledge representation and making use of the idea of fuzzy constraint processing to model practical dynamic control systems. Finally, simulation results show that a FCC achieves equivalent performance as PD type and PI type FLCs and also demonstrates superior outcomes to a conventional Proportional-Integral-Derivative (PID) controller in terms of rise time and peak percent overshoot .