Adaptive fuzzy PI controller for permanent magnet synchronous motor drive based on predictive functional control

The high-performance speed control is hard to achieve for the permanent magnet synchronous motor (PMSM) drive system under uncertain disturbances, input saturation, and system delay. To address this challenge, a novel adaptive fuzzy proportional-integral (AFPI) control scheme is investigated in this paper. An anti-saturation PI (ASPI) controller is proposed serving as the main control unit that drives PMSM to track the desired profiles, which is optimized online by a designed adaptive fuzzy tuner. Specifically, together with the parameter update constraints, an improved anti-integral saturation mechanism is suggested for the ASPI controller. Meanwhile, the adaptive fuzzy tuner with the selftuning input domain enhances the optimization ability to effectively tackle the system uncertainties. Then, a predictive functional control method is incorporated into the tuner to mitigate the control lag caused by error-driven characteristics, which ensures the dynamic tracing control performance in the presence of system delay. The stability and the H infinity robustness of the AFPI controller are guaranteed based on D -decomposition theory. Simulations and real-time experiments are performed, and the results illustrate that the designed scheme has superior performance in terms of dynamic tracking control and anti-disturbance capabilities as compared to conventional methods. (c) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.