An error-based on-line rule weight adjustment method for fuzzy PID controllers

In this study, a new method is proposed for the adjustment of the fuzzy rule weights of the fuzzy PID controllers in an on-line manner. For this purpose, the transient phase of the unit response of the closed loop system is taken into consideration. The transient phase of the response is assumed to be divided into certain regions which are assigned in accordance with the number of membership functions defined for the error input of the fuzzy logic controller. Then, the relative importance or influence of the fired fuzzy rules of the fuzzy logic controller are determined for each region and the meta-rules are derived for the adjustment of corresponding fuzzy rule weight values to obtain an 'efficient' and 'appropriate' control signal that will achieve a ''desired'' system response. Since the value of system error varies during the transient system response and it is on hand for each region and sampling time, the weight tuning is accomplished using this error value. For this purpose, two simple functions based on the absolute value of the normalized system error are directly used for the assignment of the rule weights by an adequate arrangement in accordance with the meta-rules derived. By these assignments the error value is charged as the tuning variable of the rule weights and thus an on-line self tuning rule weight assignment is accomplished. The effectiveness of the proposed self tuning method is demonstrated on linear and non-linear systems by simulations and a real time application is done on Process Control Simulator.