| The Permanent Magnet Synchronous Motor(PMSM)is an AC motor with a simple structure,high power density,and strong overload capacity.It has become a popular choice in various industries due to its superior performance,which has further driven research and development of its control technology.However,during actual operation,the Permanent Magnet Synchronous Motor is easily affected by various nonlinear factors such as changes in environmental temperature and magnetic circuit saturation,causing the main electromagnetic parameters of the motor continuously changes,adding difficulty to the establishment and analysis of mathematical models in dynamic operation of the motor.At the same time,the PI controller is widely used in motor control systems,but fixed PI controller parameters cannot be dynamically adjusted with the changes of electromagnetic parameters.Therefore,the research of this paper focuses on the online identification of the parameters of the PMSM,and based on this,designs a fuzzy adaptive PI controller that can adjust with changes in motor parameters,so that the control system has better adaptability and robustness.The main research content of this paper is as follows:Firstly,in order to improve the control performance of Permanent Magnet Synchronous Motors,the structure and mathematical model of PMSM is analysed in this paper.Then,based on the performance requirements of the control object and the system,the vector control strategy with direct axis current i_d=0 is selected,and provides an in-depth description of the space vector pulse width modulation technique.Finally,a simulation model of PMSM current-velocity double closed-loop vector control system is built in Simulink to verify the effectiveness of this control method.Secondly,the factors influencing the motor parameter perturbation is analysed in this paper,and designs a parameter identification method based on Model Reference Adaptive System(MRAS).Popov hyperstable theory is used to design the adaptive law,which can identify the key electromagnetic parameters of PMSM online and improve the control accuracy of PMSM.Based on the results of motor parameter identification,a current loop-velocity loop adaptive PI controller is designed with the changes of motor parameters,which can adjust the current loop-velocity loop controller parameters in real time according to the changes of motor parameters.At the same time,in order to reduce the impact of external load and inertia changes on the control performance of the system,fuzzy control is introduced on the basis of the velocity loop adaptive PI controller.Since fuzzy control is insensitive to the change of system parameters and does not require an accurate system model,the fuzzy logic reasoning system is adopted for online auxiliary adjustment of the velocity loop adaptive PI controller parameters,so that the system has better adaptability and robustness.Finally,the designed fuzzy adaptive PI controller and adaptive PI controller are experimentally verified in Simulink to test their control performance.The simulation results show that compared with the traditional double closed-loop PI control,the adaptive PI control can achieve adaptive adjustment of the controller parameters to adapt to the changes of the internal parameters of the motor,so that the system controller can maintain the quasi-optimal PI parameters.In addition,when the external load and inertia change,the addition of fuzzy control is more effective in suppressing the adverse effects of such changes on the system,thus improving the system’s anti-interference and stability. |
