Adaptive fuzzy output feedback and command filtering error compensation control for permanent magnet synchronous motors in electric vehicle drive systems

In this paper, under the circumstance of parametric uncertainties and external load disturbance, an adaptive fuzzy output feedback and command filtering error compensation control is proposed for permanent magnet synchronous motors (PMSMs) in electric vehicle systems. First, fuzzy logic systems (FLSs) are used to approximate unknown nonlinear functions, and a fuzzy reduced-order observer is set up to estimate the angle speed of the PMSMs. Then, the command filtering error compensation control is utilized to handle the explosion of complexity problem arose from the derivation of virtual control functions and reduce the error caused by the command filter, which improves the control accuracy. In addition, the adaptive backstepping technique is exploited to construct the adaptive fuzzy controllers to guarantee the tracking error converge to a small neighborhood of the origin. Finally, simulation results verify the effectiveness and advantages of the proposed theoretic result. (C) 2017 Published by Elsevier Ltd on behalf of The Franklin Institute.