Multi-objective Optimal T-S fuzzy Controller of Nonlinear Permanent-Magnet Synchronous Motor for Speed Tracking

This paper investigates the multi-objective control of the nonlinear permanent magnet synchronous motor (PMSM) system. To this end, the T-S fuzzy approach is introduced to tackle the synthesis of the speed control under nonlinear dynamics. Then, a novel multi-objective bat algorithm (NMOBA) is proposed for optimizing the constructed T-S fuzzy controller. Specifically, the virtual desired variables are utilized for developing the fuzzy tracking control to trace the desired speed profiles. Theoretical analyses demonstrate that the proposed control strategy can simplify the nonlinear controller design. Furthermore, the challenge in the optimization of the T-S fuzzy controller is addressed, that is, complex adjustable parameters usually lead to multiple local optima. To avoid premature convergence without losing efficiency, the hybrid mechanism is designed for the proposed NMOBA to enhance convergence and diversity of the swarm. Experimental results on a real-world PMSM system illustrate that the proposed controller has a significant advantage over the traditional LMI-based T-S fuzzy controller.