Design And Simulation Research Of BLDC Motor Control System Based On STM32

In recent years, with the rapid development of electronic power technology and modern control theory, the control and application of motor have been a research content that people pay more and more attention in. In general, motors are mainly divided into two kinds:alternating current machines and direct current machines. AC machine has the advantages of simple structure, low manufacturing cost and so on, and is widely used in various fields, such as machine tools and mechanical processing equipment. However, due to the relatively poor speed and start-up performance of the AC motor, the AC motor is rarely used in the place where the speed and torque are strictly required. Comparing with the AC motor, DC motor has fast rotated speed and large torque. So it is treated as the main object in many occasions. In this paper, it mainly studies the one type motors named brushless DC motor.Brushless DC motor is a new kind of motor that comes with the rise of motor technology and permanent magnet material. It is a special form of DC motor and has the advantages of small volume, high efficiency, good speed regulation, simple control and easy to realize the digital control, so it is widely applied in many fields. Therefore, the study of Brushless DC motor control system has a very far-reaching significance.First of all, the paper establishes a mathematical model of brushless DC motor control system. In the control scheme, it establishes the double closed-loop control scheme of external rotating speed and internal current through the comparative study analysis.Next is the modeling and Simulation of Brushless DC motor control system. The paper built a simulation model of each function model by using the powerful computing analyze ability of MATLAB in Simulink environment. System adopts traditional PID control, Fuzzy PID control based on particle swarm optimization algorithm and Fuzzy PID control based on improved particle swarm optimization algorithm three different ways to optimize and improve the speed controller. The current loop is still using PID to control. The simulation results show that the Fuzzy PID brushless DC motor control system based on Improved Particle Swarm Optimization Algorithm has overshoot is far less than 0.5%, rising faster, and rise time than the former enhance about 0.003s, stability and recovery only 0.001s and so on. It is better than the Fuzzy PID control based on particle swarm optimization algorithm and the common PID control.At last, there are the implementation and experimental validation of brushless dc motor control system. Due to the STM32 has the advantages of low cost, high efficiency and high integration, so by using STM32 to build the control system of brushless DC motor, it can greatly simplifies the structure of system, enhances the system performance to meet the needs of more occasions. On the basis of analyzing and summarizing the problems existing in the control strategy of brushless DC motor, through the research and analysis of the brushless DC motor control system and on the basic of comparing the control chips, the paper determines the control system that make STM32RBT6 as the core. In the control strategy, the system uses the advanced algorithm based on the improved particle swarm optimization algorithm to combine the improved particle swarm optimization (quantum behaved particle swarm optimization) with Fuzzy PID controller(Fuzzy-PID), which makes the control system not only have the advantages of fast convergence and avoiding premature of the quantum behaved particle swarm optimization algorithm, but also have the characteristics of flexible and strong adaptability of Fuzzy PID controller. The paper uses Altium Designer software to complete the hardware schematic of the brushless DC motor control system and PCB board design, and designs the flow chart of general program and interrupt subroutine. Then base on the flow chart, to complete the program of each part of the system and then realize the control of rotating speed of brushless DC motor and other parts with IR IR2110S driving chip together. Experiments show that, according to the current state of the control system of brushless DC motor, the Fuzzy PID control based on improved particle swarm optimization algorithm can adjust the three parameters online automatically, which can obviously improve the control performance of the brushless DC motor system.