Optimal Fuzzy-Immune-PID Controllers Design of PWM DC-DC Converters

Abstract

Generally, the state-space averaged model, which is an approximate model, is employed to synthesize the PWM (pulse-width-modulated) DC-DC converters. Instead, an algorithm based on orthogonal-functions approach (OFA) only involving algebraic computation is proposed in this paper to precisely solve the discontinuous dynamic equations of the PWM DC-DC converters. On the other hand, to accommodate the load variation of a PWM DC-DC converter, a fuzzy-immune-PID controller by fusing the conventional PID controller, the fuzzy logic theory and the immune feedback law is considered as a self-adaptive controller in this paper. Based on the OFA, the optimal fuzzy-immune-PID controller design problem for a class of PWM DC-DC converters is transformed into a static-parameters optimization problem represented by algebraic equations. Then for the static optimization problem, the hybrid Taguchi-genetic algorithm (HTGA) is employed to find the optimal parameters of the fuzzy-immune-PID controllers for the PWM DC-DC converters under the criterion of minimizing an integral quadratic performance index. The proposed integrative method, which fuses the OFA and the HTGA, is non-differential, non-integral, straightforward, and well-adapted to computer implementation. The results show that the proposed method gives an effective way for synthesizing the optimal parameters of the fuzzy-immune-PID controllers of the PWM DC-DC converters.