A multiple tuning fuzzy control system design

A multiple tuning method is proposed to develop fuzzy control system such that the output of the controlled system has the desired output without knowing the mathematical model of the controlled system. In this control structure, a multiple tuning algorithm based on the technology of reinforcement learning and decision making algorithm is constructed to enable it to tune the consequent parameters of the fuzzy controller such that the fuzzy controller has the self-tuning ability. In this multiple tuning method, a state evaluator is considered to play the role of a critic element to evaluate the current state of the controlled system. A functional-type evaluator is used to produce a scalar value, which is provided to a parameter modifier to tune the adjustable parameters of the fuzzy controller. A decision making algorithm work as a selector to select a appropriate parameter and fed a better action to the plant such that the controlled system has a better performance. The goal of the multiple tuning algorithm is to maximize the evaluation value of the current state such that the control objective can be attained. Finally, the inverted pendulum control problem is used to illustrate the effectiveness of the proposed control system structure.