Development of an intelligent fuzzy controller

The paper is concerned with two types of fuzzy PID controllers, the rule-based fuzzy PID controller and the learning fuzzy PID controller. Initially, the development of the rule-based fuzzy PID controller is studied, and subsequently, the development of the learning fuzzy PID controller is outlined. For the rule-based fuzzy PID controller, the PID gains are firstly tuned using a conventional tuning method. The rule buffer of the rule-based fuzzy then readjusts the PID gains during the system operation. The learning fuzzy PID controller not only readjusts the PID gains, it also creates and updates the rules in the rule-buffer automatically during the application of the learning fuzzy PID controller to the process. The rule-based fuzzy PID controller and the learning fuzzy PID controller are both applied to a non-linear revolute-joint robot-arm for path tracking experiments. The results of the experiments for the rule-based fuzzy PID controller and the learning fuzzy controller are compared with a conventional PID controller in order to evaluate the results