The design of a fuzzy constraint-base controller for a dynamic control system

Despite the successes of rule-based fuzzy logic control, this paradigm offers only a small part of the expressive competence of the first-order predicate calculus (FOPC). 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. Hence, constraints are suitable to the task of modeling the controller in a dynamic control system so that the output is governed to a desired state as specified by the constraints. The concept of “fuzzy constraints” in problem solving is introduced and some basic definitions of fuzzy constraint processing in a constraint network are addressed. Then a fuzzy local propagation inference mechanism for reasoning about imprecise information 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 first-order logic knowledge representation and taking advantage of the idea of fuzzy constraint processing to model practical dynamic control systems. Finally, simulation results also show that a FCC achieves equivalent performance as PD type and PI type FLCs and also demonstrates superior outcomes to a conventional PID controller in terms of rise time and peak percent overshoot