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When the working environment and task of PMSM change, the model of the controlled object will change greatly. Because every time the model changes, the parameters of the controller must be adjusted. In order to adjust the parameters of the linear ADRC simply and quickly, a parameter self-tuning method based on the improved particle swarm optimization algorithm is designed. The adaptive weight factor is introduced in the algorithm, which takes into account the local search ability and global search ability of particles. In order to avoid the particle falling into the local optimal solution, the Cauchy mutation method is used to make the particle jump out of the local optimal solution and find the global optimal solution. Simulation results show that the improved PSO algorithm can achieve better control effect.