Parameters Self-regulating Gray Predictive Control Of The Brushless DC Motor Based On DSP

With the advancement of technology, digital signal processor (DSP) technology in the past 10 years have made rapid development. Because DSP performance-cost ratio rising in recent years, DSP has been used extensively in each fields of the national economic life.For meeting the needs of market, The TI company has put out special-purpose TMS320LF24x series of DSP for automation and motor control, and has made enormous success. The BLDCM with its superior performance, has been widely applied in various fields.Currently, no position sensor brushless DC motor (BLDCM) electric drive system is a hot research field. However, to improve the performance of the system is faced with many difficult problems. In this paper, the problems of sensorless brushless Permanent Magnet Brushless DC Motor are studied. And a controlling method is designed well.Based on the analysis of mathematical model for BLDCM, a model is proposed with simulation package MATLAB. The simulation results show the good dynamic and stationary performance. It can test the feasibility of new method to promote the design of real system.First, it will analyze structure and the work principle of brushless DC motor,then study the essence structure and the work principle of sensorless brushless DC motor, and based on the model of dynamic state mathematics subsequently, according to Matlab/simulink, set up the independent function model. By carrying on the organic integration of the model, it will simulate brushless DC motor really.Second, using China scholar Professor Deng Julong created gray control theory will improve the traditional motor PID control. Grey prediction is used to predict the speed of BLDCM. This control system can automatically adjust the speed controller parameters according to the grey precision of grey prediction.we can use it to control the brushless DC motor speed. By carrying brushless DC motor on the organic integration of the model, it will simulate really. This approaches actual to debugging, also for the system more, speeding a design and adjusting follow-up research foundation.This paper mainly study some pivotal techniques—position detection, start and control method, which surrounds brushless DC motor (BLDCM) without position sensor control system's design. In order to improve the speeding performance, we adopt the two closed-loop to control strategy of speed and current. The PI speed and current controller are used to control the BLDCM. Grey prediction is used to predict the speed of BLDCM. This control system can automatically adjust the speed controller parameters according to the grey precision of grey prediction. The MCU of system is the TMS320LF2407 DSP chip. In virtue of powerful processing capacity and plenty peripherals of DSP, the system adopt more reasonable software structure instead of the former complicated hardware circuit, and get better dependability.Experiments show that the motor start fast and stable with wider area of speeding. This BLDCM control system has the features of simple structure, high dependability, and can be used in many fields.This has made much useful trying of the theory and practice in the control field for the app.lications of gray prediction theory. Gray forecast results show the accuracy and rapidity. It has amended and improved conventional PID control strategy.