Compared with ordinary DC motors,the biggest feature of brushless DC motors(BLDCM)is that they use electronic circuit commutation instead of brush commutation,which overcomes the shortcomings of traditional DC motors such as high noise and easy wear,while retaining It has the advantages of large starting torque,good speed regulation performance and easy control of traditional DC motors.Therefore,it is widely used in instrumentation,new energy vehicles,smart home,heavy industry and other fields.Compared with the common DC motor control system,the brushless DC motor control system is a control system with strong nonlinearity and high coupling.The common PID control algorithm cannot guarantee the good dynamic and static performance of the brushless DC motor control system,while the fuzzy control algorithm has the advantage of combining expert experience and engineering practice without relying on the system model.In view of the advantages and disadvantages of the two algorithms,this paper designs an improved fuzzy-PID control algorithm for the control of brushless DC motors,and simulates and experiments the designed control system on the matlab simulation software and hardware experimental platform respectively.Analysis of simulation and experimental data results verifies that the designed control system has short adjustment time,small overshoot,and good dynamic and static performance.The main work of this paper can be summarized as follows:1.The basic principle of the brushless DC motor control system is analyzed and the mathematical model of the brushless DC motor is established.Firstly,the components of BLDCM control system are briefly analyzed;then the working principle of BLDCM is analyzed in detail;finally,the mathematical modeling of BLDCM is carried out,including voltage equation,torque equation,motion equation,etc.,and BLDCM is briefly described The principle of speed regulation provides a theoretical basis for the design of each module of the subsequent BLDCM control system.2.Analyze the advantages and disadvantages of various algorithms,design an improved fuzzy-PID control algorithm,and build a motor simulation platform in MATLAB simulation software.Firstly,the control structure of the BLDCM control system is analyzed and selected;then the advantages and disadvantages of the PID algorithm and fuzzy control algorithm are compared respectively.By fully combining the advantages of the two algorithms,a fuzzy PID control algorithm with variable universe of universe is designed for the control of the BLDCM control system.Finally,the simulation model of the control system is built in MATLAB/SIMULINK simulation software and run.The running results verify that the improved control algorithm has good dynamic and static characteristics.3.Completed the hardware circuit construction and software writing of the brushless DC motor.In terms of hardware circuit: firstly,the digital signal processor of the main control chip of the brushless DC motor was selected and each circuit of the TMS320F28335 minimum control system was designed,including the power supply module,JTAG module,clock circuit module,reset circuit module,etc.;The peripheral circuits of the BLDCM control system include ADC sampling module,position signal capture module,drive circuit module,inverter circuit module,etc.In terms of software programming: the main program module,motor startup module and interrupt module including capture interrupt module,ADC sampling interrupt and motor speed controller interrupt module are designed by modular design idea.4.Completed the experimental demonstration of the brushless DC motor control system and came to a conclusion.Experiments were carried out in the established BLDCM experimental platform,and various data of the experimental platform were sampled by RIGOL oscilloscope,including the motor speed signal,position signal,current signal and voltage signal.After analyzing the sampled experimental data,it is verified that the control algorithm and BLDCM control system designed in the paper have good control performance,and the superiority of the designed control system is verified. |