Research on adaptive fuzzy-sliding optimization control of servo system

To improve dynamic and static performance of brushless direct circuit motor(BLDCM) position servo system,a new controller design method based on optimum linear quadratic regulator(LQR) strategy was proposed.The controller was composed of optimum LQR,fuzzy controller and sliding mode adaptive regulator.According to status transform and Lyapunov stability theory,optimum LQR initial value obtained by off-line computation was taken as the fuzzy controller input,and system fuzzy parameters were regulated by adaptive sliding mode to decrease the Lyapunov objective function.Experiments on the proposed controller were simulated under idle load,load and changing motor parameters.The simulation results show that the controller designed by the proposed method obviously improves the dynamic and static performance,ability of disturbance rejection and robustness of the BLDCM position servo system.The position output tracks the reference position rapidly and smoothly.