Self-tuning interval type-2 fuzzy PID controllers based on online rule weighting

In this study, a self-tuning method is proposed for interval type-2 fuzzy PID (IT2FPID) controllers. The proposed method tunes the fuzzy rule weights of the IT2FPID controllers in an on-line manner. The step response of the closed loop system is firstly taken into consideration and the response is divided into certain regions which is equal to the number of fuzzy sets defined for the error input of the IT2FPID controller. Moreover, the relative importance of the activated fuzzy rules is determined for these regions. We will present meta-rules for tuning of the fuzzy rule weights in order to obtain an appropriate control signal that will achieve a satisfactory system response. In this context, we will use two simple functions for the tuning of the rule weights of IT2FPID controller structure. The effectiveness of the proposed self-tuning IT2FPID is demonstrated on a real time ball and beam setup. The results illustrated that the proposed type-2 fuzzy controller gives a simple opportunity to enhance the control performance in comparison with the T1FPID and IT2FPID controller structures.