Research On PMSM Control Based On Advanced Control Theory

With the development of science and technology, Permanent Magnet Synchronous Motor (PMSM) get a wide range of applications for its superior performance. Especially in the control of requiring high precision and high reliability, such as aeronautics and astronautics, machining centers, robotics control, permanent magnet synchronous motor has been gradually replacing DC motors and become the mainstream. At the same time, our country is rich in rare earth resources, which makes the research of permanent magnet synchronous motor has become an important research content and hot spots.PID control of its simple structure, high reliability and ease of project implementation at industrial control, etc. have been widely used. Change in the system model parameters is not the case, you can get good control. But Permanent Magnet Synchronous Motor is a typical example of many variables, parameters time-varying and strong-coupling control systems, it is difficult to establish a precise mathematical model of the system, if we reuse the traditional PID controller to control the system, it's not easy to get an ideal control effect .In recent years, with a lot of research on the advanced control theory, the control of Permanent Magnet Synchronous Motor system has opened new avenues. Artificial Neural Networks become a hot research with the ability of self-learning, sele-adaptive and self-organization. The neural network intelligent PID controller constituted by combinating Artificial neural network with traditional PID control, can automatically adjust control parameters to adapt to the changes in system parameters.It's an effective method of resoliving the shortconmings of the traditional PID controller, such as not real-time adjusting parameter and unforcement robustness.The paper first discusses the operating characteristics and control Mechanism of Permanent Magnet Synchronous Motor,then establish the mathematical model of Permanent Magnet Synchronous Motor.On this basis, with the combination of the traditional PID control, Artificial Neural Networks will be applied to Permanent Magnet Synchronous Motor control system to overcome the shortcomings of the traditional PID controller. The simulation results show that with the use of new control system, Permanent Magnet Synchronous Motor can get a better dynamic and static performance, enhance the anti-interference ability and robustness, and achieve better control effect, lay the foundation for further study.