The Research On Sliding Mode Adaptive Control Of Permanent Magnet Synchronous Motor Based On FPGA

In recent years,permanent magnet synchronous motors have attracted attention because of their high efficiency,stable performance,strong robustness and other advantages.They are used more and more widely in the fields of electric scooters,balance vehicles and industrial robots.Permanent magnet motors can not run reliably and smoothly without a good control algorithm,so the research on high-performance control algorithms is very important in production.For motor control,there are many types of optional chips like DSP,MCU,and FPGA,all of them are used in motor control widely.FPGA is developing more and more rapidly in the field of motor control with its advantages of high speed,low development cost and repeatable programming.This paper focuses on two aspects of the permanent magnet synchronous motor: the speed control algorithm and the sensorless control algorithm.Firstly,in the aspect of speed control algorithm,in the face of traditional speed controllers such as PI controllers,which have problems such as overshoot,complex parameter adjustment,and sensitivity to external interference,sliding mode control algorithms are favored for their strong anti-interference ability and rapid response.In this paper,an adaptive sliding mode speed controller is designed based on sliding mode control algorithm.The controller uses the RBF neural network to reduce the chattering problem caused by the sliding mode algorithm to a certain extent,and is implemented on the Simulink platform.Simulation experiments are carried out,and the experimental results prove that the sliding mode speed controller designed this time has a certain degree of advancement;after that,this paper discusses the sensorless control algorithm,in order to solve the high cost caused by the position sensor in the motor control system.Many sensorless control algorithms have been invented.This paper focuses on the sliding mode observer method,uses RBF neural network to improve the traditional sliding mode observer,and conducts simulation experiments in Simulink.The experimental results shows that the sliding mode observer designed this time has made certain progress in estimation accuracy and observation effect.Finally,the main function modules of the motor control system are designed and implemented on the FPGA platform.Aiming at the vector control strategy in motor control,the coordinate transformation module(Clark transformation,Park transformation),SVPWM module,PID control module and sliding mode control module are programmed in Verilog HDL language,and the Modelsim simulation is carried out.The simulation results prove the correctness and feasibility of the design of the system.