Active Disturbance Rejection Control of Permanent Magnet Synchronous Linear Motor Based on Improved Particle Swarm Optimization Algorithm

Permanent magnet linear synchronous motor (PMLSM) has become the key to precision linear drive systems due to its precise positioning, high thrust density and fast dynamic response. Therefore, in order to overcome the problem that the PMLSM active disturbance rejection control (ADRC) system is difficult to adjust the parameters according to experience to select the parameters, an ADRC strategy based on improved particle swarm optimization algorithm is proposed. Aiming at the particles whose current fitness value is higher than the average fitness value of the current population, the crossover and mutation mechanism of genetic algorithm is introduced, and an adaptive dynamically adjusted inertia weight and learning factor are proposed to balance the global search ability and local search ability of PSO algorithm. At the same time, the parameters of ADRC are adjusted by this algorithm. In addition, the strategy is simulated and analyzed in MATLAB / Simulink, which proves that the parameters obtained by the improved particle swarm optimization algorithm have better anti-interference performance.