Multi-objective optimization of active disturbance rejection control parameters for PMSM based on improved MOPSO

Abstract Aiming at the difficulty of manually tuning parameters in the active disturbance rejection control (ADRC) of permanent magnet synchronous motors (PMSM), a PMSM ADRC strategy based on the improved multi-objective particle swarm optimization (IMOPSO) algorithm is proposed. This strategy employs Chebyshev’s chaotic initialization for population initialization and introduces adaptive inertia weight and learning factors to enhance the algorithm’s search efficiency and the uniformity of solution set distribution. MATLAB simulations prove that this algorithm has a good tracking effect on the given signals improves the dynamic performance of PMSM and enhances their anti-disturbance ability.