A self-tuning fuzzy control system design

A self-tuning fuzzy control system is proposed such that the controlled system has the desired output without knowing the mathematical model of the system. In this control structure, a parameter tuning algorithm based on the technology of reinforcement learning and decision making is constructed to enable it to tune the consequent parameters of the fuzzy controller such that the fuzzy controller has a self-tuning ability. In this paper, a state evaluator is considered to play the role of a critical 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 mechanism works as a director to select an appropriate parameter and get a better action such that the controlled system has better performance. The goal of the parameter 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