Brushless DC motor ( BLDCM) speed servo system is multivariable,nonlinear and strong coupling. The parameter variation, the cogging torque and the load disturbance easily influence its performance. Therefore,it is dif...Brushless DC motor ( BLDCM) speed servo system is multivariable,nonlinear and strong coupling. The parameter variation, the cogging torque and the load disturbance easily influence its performance. Therefore,it is difficult to achieve superior performance by using the conventional PID controller. To solve the deficiency,the paper represents the algorithm of active-disturbance rejection control ( ADRC) based on back-propagation ( BP) neural network. The ADRC is independent on accurate system and its extended-state observer can estimate the disturbance of the system accurately. However,the parameters of Nonlinear Feedback ( NF) in ADRC are difficult to obtain. So in this paper,these parameters are self-turned by the BP neural network. The simulation and experiment results indicate that the ADRC based on BP neural network can improve the performances of the servo system in rapidity,control accuracy,adaptability and robustness.展开更多
针对无刷直流电机BLDCM(brushless DC motor)的精确控制和快速动态响应的需求,设计了一种新型集成式DRV8301驱动BLDCM的控制器。在分析PID控制算法的基础上,采用增量型PID算法实现速度闭环调节;采用TMS320F28035型DSP为控制器主控芯片,...针对无刷直流电机BLDCM(brushless DC motor)的精确控制和快速动态响应的需求,设计了一种新型集成式DRV8301驱动BLDCM的控制器。在分析PID控制算法的基础上,采用增量型PID算法实现速度闭环调节;采用TMS320F28035型DSP为控制器主控芯片,设计了高集成度的驱动保护电路、三相桥式逆变电路以及转子位置检测电路,简化了硬件电路结构,并完成了控制器的软件设计。实验结果验证了所设计的BLDCM控制器具有良好的控制精度和动态响应性能。展开更多
针对具有双通道结构的无刷直流电动机(BLDCM,Brushless DC Motor)容错系统的高可靠性要求和大范围调速特点,在不增加额外设备的条件下,通过分析两个通道中功率电路直流母线电流波形的特点,提出一种采用归一化快速傅里叶变换(FFT,Fast Fo...针对具有双通道结构的无刷直流电动机(BLDCM,Brushless DC Motor)容错系统的高可靠性要求和大范围调速特点,在不增加额外设备的条件下,通过分析两个通道中功率电路直流母线电流波形的特点,提出一种采用归一化快速傅里叶变换(FFT,Fast FourierTransform)方法提取频率特征,再结合基于规则的专家系统进行故障检测与识别的方法,并通过实际电动机系统的试验验证了方法的正确性.试验结果表明:规一化FFT方法可以消除不同转速和不同负载对判断结果的影响;专家系统中阈值的选取可以有效避免实际应用中出现的噪声等因素的影响.算法复杂度低,可靠性高,易于应用,具有很强的实际操作性.展开更多
文摘Brushless DC motor ( BLDCM) speed servo system is multivariable,nonlinear and strong coupling. The parameter variation, the cogging torque and the load disturbance easily influence its performance. Therefore,it is difficult to achieve superior performance by using the conventional PID controller. To solve the deficiency,the paper represents the algorithm of active-disturbance rejection control ( ADRC) based on back-propagation ( BP) neural network. The ADRC is independent on accurate system and its extended-state observer can estimate the disturbance of the system accurately. However,the parameters of Nonlinear Feedback ( NF) in ADRC are difficult to obtain. So in this paper,these parameters are self-turned by the BP neural network. The simulation and experiment results indicate that the ADRC based on BP neural network can improve the performances of the servo system in rapidity,control accuracy,adaptability and robustness.
文摘针对无刷直流电机BLDCM(brushless DC motor)的精确控制和快速动态响应的需求,设计了一种新型集成式DRV8301驱动BLDCM的控制器。在分析PID控制算法的基础上,采用增量型PID算法实现速度闭环调节;采用TMS320F28035型DSP为控制器主控芯片,设计了高集成度的驱动保护电路、三相桥式逆变电路以及转子位置检测电路,简化了硬件电路结构,并完成了控制器的软件设计。实验结果验证了所设计的BLDCM控制器具有良好的控制精度和动态响应性能。
文摘针对具有双通道结构的无刷直流电动机(BLDCM,Brushless DC Motor)容错系统的高可靠性要求和大范围调速特点,在不增加额外设备的条件下,通过分析两个通道中功率电路直流母线电流波形的特点,提出一种采用归一化快速傅里叶变换(FFT,Fast FourierTransform)方法提取频率特征,再结合基于规则的专家系统进行故障检测与识别的方法,并通过实际电动机系统的试验验证了方法的正确性.试验结果表明:规一化FFT方法可以消除不同转速和不同负载对判断结果的影响;专家系统中阈值的选取可以有效避免实际应用中出现的噪声等因素的影响.算法复杂度低,可靠性高,易于应用,具有很强的实际操作性.
