This study presents a novel controller by employing fuzzy-sliding mode control and genetic algorithms equipped with a modified evolutionary direction operator for optimal position control with an induction motor. Applying the sliding mode control technique provides the proposed controller with many advantages, such as a small overshoot, tiny steady-state error, rapid response, and adaptability to equipment parameters variation and external disturbance. The genetic algorithm optimizes the parameters of fuzzy membership functions defined according to expert experience, and its supplementary modified evolutionary direction operator determines improved search directions. The proposed approach is applied to a position servo system. Computational results indicate that the proposed controller exhibits excellent performance with all the advantages mentioned above. Moreover, the proposed controller is immune to the chattering problem that typically affects general controllers.
['Ching-Tzong Su', 'Guor-Rurng Lii', 'Hong-Rong Hwung']
POSITION CONTROL EMPLOYING FUZZY-SLIDING MODE AND GENETIC ALGORITHMS WITH A MODIFIED EVOLUTIONARY DIRECTION OPERATOR