An improved Direct Adaptive Fuzzy controller for an uncertain DC Motor Speed Control System

Duc Cuong Quach, Shuang Huang, Quan Yin, Chunjie Zhou


In this paper, we present an improved Direct Adaptive Fuzzy (IDAF) controller applied to general control DC motor speed system. In particular, an IDAF algorithm is designed to control an uncertain DC motor speed to track a given reference signal. In fact, the quality of the control system depends significantly on the amount of fuzzy rules-fuzzy sets and the updating coefficient of the adaptive rule. This can be observed clearly by the system error when the reference input is constant and out of a particular range or in the case of it varies with nonzero acceleration. So, in order to enhance quality of the system, increasing the amount of fuzzy sets and adjusting appropriately the updating coefficient of controller based on value of state error vector are needed. In addition, the proposed IDAF algorithm can control the DC motor speed under unstable supply voltages and varying loads. The control system is implemented on a dsPIC33FJ256MC710A 16-bit DSC (Digital Signal Processing Controller) board. Experimental results demonstrate the effectiveness of the proposed method.



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