Optimization Design Of PMSM Servo System Based On Advanced Control Algorithm

In the industrial production,high precision servo system is widely used.As an significant part of AC servo system,permanent magnet synchronous motor(PMSM)plays a pivotal role,especially for the high positioning precision field.The goals of this paper are to improve the performance of PMSM servo system,and the main research topics are high performance current decoupling controller design and high performance algorithms in speed loop and position loop.The details are as follows:(1)By analyzed the currently mainstream servo products development trend,it could be summarized the main control strategies and key technologies of permanent magnet synchronous motor servo system.The vector control strategy is adopted,established the mathematical model of permanent magnet synchronous motor.On this basis,the principle and implementation of space vector pulse width modulation(SVPWM)technology are described in detail.(2)The three closed loop structure of permanent magnet synchronous motor servo system and parameters of current loop,speed loop and position loop controller are designed.Aiming at the problem of electromotive force coupling in the current loop,the decoupling controller based on internal model control(IMC)and voltage feed-forward control(VFDC)are designed.Because the voltage feed-forward decoupling control strategy is easily affected by the change of parameters,an internal model control method is adopted to design a current loop controller which combines the internal model control with the voltage feed-forward decoupling.To realize the complete decoupling of the electromotive force,the internal model principle is used to adjust the PI parameters of the voltage feed-forward decoupling controller,and the results are applied to the voltage feed-forward decoupling controller.Aiming at system overshoot caused by integral saturation,an integral clamped current loop decoupling controller is designed with integral clamping method.The concept of active damping is introduced to adjust the parameters of the speed loop regulator to further enhance the responsiveness and robustness of the servo system.(3)In view of the problem that the dynamic performance of the internal model control and the quality of the system control are reduced due to the time-varying parameter of the model controller and the motor model in the actual operation of the motor,a RBF neural network is proposed to approach the PMSM model,and the parameter selection energy index is used to train the parameters ? of the internal model controller,to realize adaptive control of closed loop system.(4)Optimized speed loop and position loop of PMSM servo system.The parameters of the controller and the model are mismatched by the parameter changes during the system operation,and the parameters of the speed loop regulator and the position loop regulator are designed by using the genetic algorithm with the optimal preservation strategy.The feasibility of designing servo system is verified by simulation.