【作者】 周健；

【导师】 王辉；

【作者基本信息】 湖南大学 ， 电力电子与电力传动， 2006， 硕士

【摘要】 由于无刷直流电机(BLDCM)的经典数学模型在系统性能分析和控制应用中存在不足之处,本文提出了一种新型数学模型。本文基于经典的相电压模型,导出线电压模型,然后推出相电流模型,并给出相电流模型解的表达式。本文还用MATLAB/Simulink中的PSB模块创建一个新型实用BLDCM仿真模型,作为系统特性分析与新控制策略研究的基础。本文提出了一种利用扩展卡尔曼滤波器算法来估计BLDCM的转速和位置的方法。在直流无刷电机的原理基础上,利用扩展卡尔曼滤波器将转子转速和位置看成系统的两个状态变量,根据定子侧可测的电流、电压值,逐步估计出转子转速和位置,为无速度和位置传感器无刷直流电机控制系统打下基础。仿真结果证明了所提出方法的可行性。本文详细地阐述了BLDCM换相转矩脉动产生的原因,并介绍了电机在低速和高速运行时换相转矩抑制的方法。提出了一种采用直流侧电流反馈控制的BLDCM换相转矩脉动抑制方法,这种方法将无差拍电流控制器和换相补偿相结合。仿真试验证明所提出换相转矩脉动抑制技术的有效性。本文基于BLDCM的动态模型提出了一种性能较好的递归模糊神经网络(RFNN)无速度传感器BLDCM控制方法,采用RFNN控制器作为转速控制器来近似最优控制器输出。仿真结果表明,当系统参数动态变化或受到外部不确定因素影响时,利用神经网络来在线调整网络的隶属函数参数以及神经网络递归权值,使系统具有良好的动静态性能。更多还原

【Abstract】 A novel mathematical model for Brushless DC Motor (BLDCM) is proposed to meet the requirements of practical analysis and control application. Based on classical phase voltage model, a line voltage model is derived and then the phase current model is obtained. Beside, the solution for this novel mathematical model is also given. A novel simulation model of BLDCM is built, by using MATLAB/Simulink PSB block, to help the characteristics analysis and promote the research of new control strategies.A novel method for speed and rotor position estimation of BLDCM,which applies extend Kalman filter (EKF), is presented in this paper. The rotor velocity and position can be taken as two states variable of the system by using the EKF on the basis of the theory of the BLDCM. Based on the measured stator currents and stator voltages, we can estimate the rotor velocity and position. It is very useful for us to study the application of the velocity and position sensorless operation of brushless DC motor drives. The simulation results have confirmed the feasibility of the presented technique.This paper analyses the producing reason of commutation torque ripple, introduces the reason of commutation torque ripple suppression techniques that are practically effective in low speed and high speed. A method for reducing commutation torque ripple generated in BLDCM using a single DC current sensor, which combines deadbeat current control scheme with commutation compensation techniques, is presented in this paper. Effectiveness of the proposed control method is verified through simulation.A speed-sensorless control method for BLDCM, which applies recurrent fuzzy neural network (RFNN), is presented in this paper based on the dynamic model of BLDCM. The RFNN controller is used as a speed controller to mimic the optimized output of the system. The simulation results show the good performance for the system by using network to adjust the parameters and the recurrent weight of neural network on-line dynamically on the condition of variety of system parameter and the impact of outside uncertainty factors.更多还原