摘要
科技日新月异，数字信号处理器(DSP)技术在过去的十多年里取得了飞速的发展，由于DSP的性价比不断提高，已经开始大量应用于国民经济生活的各个领域。美国TI公司为适应市场的需要，针对电机控制领域推出了专用TMS320LF24x系列DSP，并取得了巨大的成功。无刷直流电机(BLDCM)以优越的性能，被广泛地应用于各个领域。
目前，无位置传感器无刷直流电动机(BLDCM)系统是电气传动领域研究的热点，但要进一步提高该系统的性能仍然存在许多难点问题。本文针对其中一些关键问题进行分析和研究，提出了相应的控制方案。在分析无刷直流电动机动态数学模型的基础上，该系统模型显示出良好的动、静特性，对于改进实际控制系统提供了方便。
首先，分析了无刷直流电机的本体结构和工作原理，进而阐明无位置传感器无刷直流电机的本体结构和工作原理，构建其动态数学模型，又基于Matlab／simulink对其构建独立的功能模块，再进行模块的有机整合，来进行建模仿真，这更加逼近实际系统，加快了设计和调试过程。
其次，利用我国学者邓聚龙、陈绵云创立的灰色控制理论，对传统电机PID控制策略进行改进，用灰色预测实现速度预测，该控制系统根据预测精度来自动调整速度控制器参数，以此来控制无刷直流电机转速调节。基于Matlab／simulink对其进行建模仿真，观察其动、静态特性，对结果进行了讨论。构建试验平台，以证明其理论的可行性和合理性。
本文围绕无位置传感器无刷直流电机(BLDCM)控制系统设计中的几个关键技术：位置检测、起动和控制方法进行了深入的研究。为了提高系统的调速性能，控制方法采用了转速、电流双闭环，使用PI进行速度和电流控制，用灰色预测实现速度预测，该控制系统根据预测精度来自动调整速度控制器参数。控制系统设计采用TI公司TMS320LF2407x系列的DSP芯片作为控制核心。借助于DSP强大的处理能力和丰富的外设，整套系统省去了以往复杂的硬件电路，采用结构更加合理的软件实现了系统的大部分功能，从而提高了系统的可靠性。
实验结果表明该控制系统还具有结构简单、电机起动快速、稳定，具有较宽的调速范围。同时，该系统可靠性高等特点，具有广泛的应用前景。为灰色预测理论在控制领域的应用做了有益的理论和实践尝试，表明灰色预测的准确性和快速性，对于修正和改进传统PID控制策略有显著的作用。
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.
引文
[1] 张琛著．直流无刷电动机原理及应用[M]．北京：机械工业出版社，2001．
[2] 石山．永磁无刷直流电动机设计理论及其DSP控制技术的研究：[西安交通大学博士学位论文]．西安：西安交通大学，2003
[3] Lee C K, Kwok N M. A variable structure controller with adaptive switching surfaces [brushless DC motor]. In: Proceedings of the American Control Conference. Seattle, 1995.1033-1034
[4] Lee C K, Pang W H. A brushless DC motor speed control system using fuzzy rules. In: Fifth International Conference on Power Electronics and Variable-Speed Drives. London, 1994.101-106
[5] 许大中，贺益康．电机控制[M]．杭州：浙江大学出版社，2002，164-172
[6] 敖银辉，基于DSP的无刷直流电机模糊控制系统研究[J]．《中小型电机》，2004，31
[7] Pragasan Pillay, R Krishnan. Modeling of permanent magnet motor drives [J]. IEEE Trans. on Industry Electronics. 1988, 35(4)
[8] Evans P. D, BrownD. Simulation of brushless DC drives [C]. IEEE Proceedings B, Electric Power Applications. 2001, 137(5)
[9] 何克忠，李伟．计算机控制系统[M]．北京：清华大学出版社，1998．4
[10] 傅立．灰色系统理论及其应用[M]．北京：中国科学技术文献出版社，1992
[11] 熊和金，陈绵云，瞿坦．控制系统的两类灰色模型[J]．武汉交通科技大学学报．1999．10
[12] 刘思峰，郭天榜，党耀国等．灰色系统理论及其应用[M]．北京：科学出版社，2000
[13] 张广立，付莹，杨汝清，一种新型自调节灰色预测控制器[J]．控制与决策，2004
[14] Pillay P Krishnan R. Modeling, simulation, and analysis of permanent-magnet motor drives, Part Ⅰ: Zhe permanent-magnet synchronous motor drive [J]. IEEE Trans. on Industry Applications, 1989, 25(2): 265-273.
[15] Waikar S P. A low cost low loss brushless permanent magnet motor drive [O]. The office of graduate studies of Texas A&M University: Texas A&M University, 2001
[16] Luk PC K, Lee CK, Kwok NM. Development of a low cost software package for the design of a brushless DC motor controller [C]. Proceeding from Electrotechnical Conference, 1994, 12-14
[17] Yilmaz Sorer. Direct adaptive control of permanent magnet motors[D]. The office of graduate studies of Rensselaer Polytechnic Institute: Rensselaer Polytechnic Institute, 2000
[18] Thomas machine Salem, Tim A Haskew. Simulation of the brushless DC[C]. Proceeding from System Theory, 1995, 12-14
[19] 王晓明，王玲．电动机的DSP控制[M]．北京：北京航空航天大学出版社，2004．7
[20] 季小尹，符向荣，王安丽．混合动力电动汽车用永磁无刷直流电机的设计与实现[J]．微特电机，2004，32(2)：5-7
[21] 张燕宾．SPWM变频调速应用技术[M]．北京：机械工业出版社，1998
[22] 韩安太等．DSP控制器原理及其在运动控制系统中的应用[M]．北京：清华大学出版社，2003．10．
[23] 刘和平等．TMS320LF240xDSP C语言开发应用[u)．北京航空航天大学出版社，2003．1
[24] 江思敏．TMS320LF240x DSP硬件开发教程[M]．机械工业出版社，2003
[25] 张相军，陈伯时，朱平平．直流无刷电机无位置传感器控制中反电动势过零检测算法及其相位修正[J]．电气传动，2001．2
[26] 何苏勤，王忠勇．TMS320C2000系列DSP原理及实用技术[M]．电子工业出版社，2005．7
[27] 谭建成．电机控制专用集成电路[M]．机械工业出版社，2002
[28] 贡俊，陆国林．无刷直流电机在工业上的应用和发展[J]．微特电机，2000
[29] 王秀芝，吴忠，许镇琳．高性能BLDCM交流伺服系统发展趋势及研究现状[J]．电气自动化．1996
[30] 邓聚龙．灰色系统基本方法[M]．武汉：华中理工大学出版社，1992
[31] 尔桂花，窦曰轩．运动控制系统[M]．北京：清华大学出版社，2002，5
[32] 吴守，箴英杰．电气传动的脉宽调制控制技术[M]．北京：机械工业出版社．2003
[33] 熊和金，陈绵云．灰色关联度公式的几种拓广[J]．系统工程与电子技术，2000．1
[34] 王晓明．电动机的单片机控制[M]．北京：北京航天航空大学出版社，2002
[35] 熊和金，陈德军．智能信息处理[M]．北京：．国防工业出版社，2006．6
[36] 徐华中，熊和金．灰色控制[M]．北京：国防工业出版社．2005．9
[37] 潘新民，王燕芳．单片微型计算机实用系统设计[M]．北京：人民邮电出版社，1994
[38] 熊鹰飞，陈绵云，熊和金．系统云SCGM(1，h)模型仿真及应用[J]．武汉交通科技大学学报，1999．6
[39] 陈隆昌，阎治安，刘新政．控制电机[M]．西安：西安电子科技大学出版社，2000，
[40] 徐腊梅，熊和金．无速度传感器交-交变频调速矢量控制系统的研究[J]．武汉理工大学学报(交通科学与工程版)．2001．2
[41] TMS320F240 DSP Controllers Reference Guide Peripheral Library and Specific Devices. Literature Number: SPRL1161C J1ne 1999
[42] Nikolaus P, Schibli, Tung Nguyen, and Alfred C. Rufer. A Three-Phase Multilevel Converter for High-Power Induction Motors. IEEE TRANSACTIONS ON POWER ELECTRONICS VOL. 13, NO. 5, SEPTEMBER 1998
[43] Krishna. R, Lee. S. PM Brushless DC Motor Drive with a New Power-converter Topology, IEEE Trans. Ind. APP. Vol. 33. no. 4, pp. 973-982, 4, July/Aug. 1997
[44] Yoon-Ho Lim, Yoon-San Kook, Yo Ko. A New Technique of Reducing Torque Ripple BLDCM Drives. IEEE Trans. Ind. Electronics, Vol 44, etc. no. 5, pp. 735-739, Oct. 1997
[45] Shen Jian xin. Microcomputer Based Position Sensorless Dirive for Brushless DC Motor. Power Electronics&Motion control Conf, China, 1994, 12(1): 402-407.
[46] Kenich Iizuka, Hideo Uzuhashi, Minoqu Kano, etc. Microcomputer Control for Sensorless Brush less Motor. 1EEE Transactions on Industry Applications, VOl. IA-21, NO. 4, May/June, 1985: 595-601
[47] Nobuyubo and Hironori Ohashi. DSP-Sased Adaptive control of a Brushless Motor. IEe Transaction on Indastrial Applications, VoL41, Nol, February 1994: 110-117
[48] Byoung-kuk Lee. Advanced low cost and high performance brushless DC motor drives for mass production. Texas A&M University, 1997
[49] Implementation of a Sensorless Speed Controlled Brushless DC drive using TMS320LF240. Literature Number: BPRA072 Texas Instruments Europe November, 1997