Speed Control of PMSM Based on Improved Whale Optimization Algorithm

Nonlinear, multivariable, strong coupling, etc. are the characteristics of permanent magnet synchronous motor (PMSM). In view of the low efficiency of the traditional proportional integral derivative (PID) controller and its poor adaptability to the changes of the working environment, an intelligent control method based on the improved whale optimization of PID controller parameters is proposed. In view of some shortcomings of traditional algorithms, chaos theory is introduced to generate initial population to increase population diversity and lay the foundation for global search of algorithm. In addition, the linear convergence factor is changed to nonlinear, and the adaptive inertia weight is added to improve the convergence speed and accuracy. Finally, the vector control model of PMSM is built in Matlab/simulink for simulation experiment. Through simulation and comparison, the effectiveness of the improved whale optimization algorithm (IWOA) for tuning PID parameters is verified.