PMSM Robust Controller Design Based On Parameter Identification

With the realization of vector control in PMSM driver,the requirement of load compatibility of PMSM is gradually improved.The change of load not only affects the system in the form of the change of disturbance torque,but also makes the parameters of the motor model perturb.These influences,together with the non ideal factors in the system itself,constitute the uncertainty of PMSM control system,which will lead to the performance degradation of the system,and even multiple oscillations or jitters and other unstable phenomena.In order to solve this problem,this paper designs a robust controller based on the nominal parameters and uncertainties obtained by identification,which improves its robust performance.In this paper,firstly,the mathematical model of PMSM in two-phase rotating coordinate system is established,the principle and implementation of SVPWM modulation are introduced,and the speed of PMSM is controlled by directional field vector control strategy.Starting from the system mechanism,the non ideal factors of inverter and sensor,model linearization and order reduction error,parameter perturbation and other factors are discussed and embedded in the multiplicative perturbation model.Secondly,this paper uses the least square method to identify the nominal model parameters off-line,and improves the identification method for the influence of non ideal factors on the parameter identification,so as to improve the identification accuracy of the nominal model parameters.Then,the double loop PI controller is designed based on the frequency domain index.Then,based on the tracking ability of the most effective frequency component of the input signal,combined with the multiplicative uncertainty of the model,the mixed sensitivity robust controller is designed,and the parameters of the controller are further optimized by ant colony optimization algorithm.Finally,the robust control simulation system of PMSM Based on parameter identification is built in Matlab / Simulink environment,and the model and algorithm verification are completed.The simulation results show that the algorithm proposed in this paper is effective and correct.