【作者】 桂石翁；

【导师】 熊和金；

【作者基本信息】 武汉理工大学 ， 检测技术与自动化装置， 2007， 硕士

【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。更多还原

【Abstract】 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.更多还原