Position Sensorless Control And Adaptive Speed Control Of Permanent Magnet Synchronous Motor

Permanent magnet synchronous motor(PMSM)is widely used in modern AC speed regulation system because of its simple structure,fast dynamic response,high efficiency and high reliability.However,the mechanical sensor of traditional permanent magnet synchronous motor is difficult in the installation and maintenance.It also increases the costs of the system and reduces the reliability of the system.Therefore,research of permanent magnet synchronous motor without position sensors is important.The permanent magnet synchronous motor system is multivariable,nonlinear and strong coupling.The traditional PID controller is easy to be affected by the motor parameters and external disturbance.The fluctuation of torque and speed will influence the stability of the system.Therefore,this paper proposes an adaptive PID controller based on RBF neural network for speed control.The main work of this thesis is as follows:(1)First of all,the basic structure and principle of permanent magnet synchronous motor are briefly introduced.The rotor selects the id = 0 for the field oriented control method.Then,the realization process of space vector pulse width modulation is analyzed.The simulation model of permanent magnet synchronous motor vector control system is established in Matlab/Simulink,and its feasibility is verified.(2)The basic principle of sliding mode variable structure and the conditions required for sliding mode are introduced at first.The chattering problem of traditional sliding mode observer is analyzed.A design scheme of sensorless permanent magnet synchronous motor based on improved sliding mode observer is proposed.By using improved switching function instead of symbolic switching function,the influence of sliding mode chattering on rotor position estimation is weakened.The adaptive sliding mode gain coefficient can be used to obtain better observation results.A cascaded filter based on variable cutoff frequency is constructed to suppress the adverse effects of higher harmonics.In this paper,the phase shift caused by the tangent function to estimate the rotor position is studied.A method of dynamic compensation of phase based on the change of speed is presented.(3)In this paper,a permanent magnet synchronous motor control platform based on Microchip's dsPIC33EP128MC204 controller chip is built.The software and hardware design of the system is accomplished,and the rotor position detection,speed regulation,overcurrent and overvoltage protection are realized.On this basis,RBF neural network is used to study the intelligent speed regulation.(4)In view of the fact that the traditional PID controller can not achieve satisfactory speed control in permanent magnet synchronous motor,an adaptive PID speed control method based on RBF neural network identification is proposed in this paper.The method combines the RBF neural network on-line identification technology and the adaptive PID control method to control the speed of PMSM.The simulation results show that this method has the characteristics of fast response,high accuracy and strong anti-interference ability.