A self-tuning expert fuzzy controller has been developed and applied in real time t o a process control problem. The knowledge base consists of rules describing the control law in terms of the process error and the resulting control action. Conditions and conclusions of each rule are fuzzy variables which are described through their continous membership curves. The inference engine used is the backward chaining process of the Prolog language. To implement the self-tuning property, the membership curve o f the controller o u t p u t has been changed according to an error based performance index. A control supervisor makes this tuning decision as a function of either past or predicted future set-point errors of the control system. If the current process model is considered reliable then the decision is based on the predicted setpoint error.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.