当前自适应滤波前馈控制方法中具有代表性的是滤波-X最小均方(filtered-X least mean square,简称FXLMS)算法,它通常假定干扰源可测且作为前馈控制器的参考输入,但实际振动控制过程中需要考虑控制输出反馈信号对参考信号的影响,因此滤...当前自适应滤波前馈控制方法中具有代表性的是滤波-X最小均方(filtered-X least mean square,简称FXLMS)算法,它通常假定干扰源可测且作为前馈控制器的参考输入,但实际振动控制过程中需要考虑控制输出反馈信号对参考信号的影响,因此滤波-X算法面向实际应用具有较大的局限性。针对这一问题,以机敏压电太阳能帆板结构为模拟试验对象,提出一种基于IIR(infinite impulse response,简称IIR)结构的滤波-U最小均方(filtered-U least mean square,简称FULMS)自适应滤波控制方法,着重分析了控制器结构设计、FULMS算法推理过程、试验模型结构设计、试验平台的构建及其试验验证等环节。经过与FXLMS算法对比仿真试验,笔者所设计的控制算法控制效果良好。将其进行试验验证分析,结果表明,所采用的控制器设计方法与控制算法收敛速度快,控制效果好,为自适应振动控制方法向实际工程应用提供了较好的研究基础。展开更多
基于滤波X最小均方差(filtered-X least mean square,简称FXLMS)控制方法实施振动主动控制的基本结构,提出了参考信号自提取的控制器结构和算法,直接利用系统误差信号获得对原激扰信号的一个估计,并用估计值作为自适应滤波器的参考信号...基于滤波X最小均方差(filtered-X least mean square,简称FXLMS)控制方法实施振动主动控制的基本结构,提出了参考信号自提取的控制器结构和算法,直接利用系统误差信号获得对原激扰信号的一个估计,并用估计值作为自适应滤波器的参考信号,以实现与外激扰信号的相关性。在针对控制算法进行Matlab仿真分析的基础上,构建了压电机敏柔性板试验模型和测控平台,并进行了算法验证。试验结果表明,该控制算法不仅实现了参考信号从振动结构中直接提取,并具有较快的收敛速度和良好的控制效果。展开更多
The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorit...The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorithm.The command input was corrected by weights to generate the desired input for the algorithm,and the feedback was brought into the feedback correction,whose output was the weighted feedback.The weights of the normalized LMS adaptive filtering algorithm were updated on-line according to the estimation error between the desired input and the weighted feedback.Thus,the updated weights were copied to the input correction.The estimation error was forced to zero by the normalized LMS adaptive filtering algorithm such that the weighted feedback was equal to the desired input,making the feedback track the command.The above concept was used as a basis for the development of amplitude phase control.The method has good real-time performance without estimating the system model.The simulation and experiment results show that the proposed amplitude phase control can efficiently cancel the amplitude attenuation and phase delay with high precision.展开更多
文摘当前自适应滤波前馈控制方法中具有代表性的是滤波-X最小均方(filtered-X least mean square,简称FXLMS)算法,它通常假定干扰源可测且作为前馈控制器的参考输入,但实际振动控制过程中需要考虑控制输出反馈信号对参考信号的影响,因此滤波-X算法面向实际应用具有较大的局限性。针对这一问题,以机敏压电太阳能帆板结构为模拟试验对象,提出一种基于IIR(infinite impulse response,简称IIR)结构的滤波-U最小均方(filtered-U least mean square,简称FULMS)自适应滤波控制方法,着重分析了控制器结构设计、FULMS算法推理过程、试验模型结构设计、试验平台的构建及其试验验证等环节。经过与FXLMS算法对比仿真试验,笔者所设计的控制算法控制效果良好。将其进行试验验证分析,结果表明,所采用的控制器设计方法与控制算法收敛速度快,控制效果好,为自适应振动控制方法向实际工程应用提供了较好的研究基础。
文摘基于滤波X最小均方差(filtered-X least mean square,简称FXLMS)控制方法实施振动主动控制的基本结构,提出了参考信号自提取的控制器结构和算法,直接利用系统误差信号获得对原激扰信号的一个估计,并用估计值作为自适应滤波器的参考信号,以实现与外激扰信号的相关性。在针对控制算法进行Matlab仿真分析的基础上,构建了压电机敏柔性板试验模型和测控平台,并进行了算法验证。试验结果表明,该控制算法不仅实现了参考信号从振动结构中直接提取,并具有较快的收敛速度和良好的控制效果。
基金Project(50905037) supported by the National Natural Science Foundation of ChinaProject(20092304120014) supported by Specialized Research Fund for the Doctoral Program of Higher Education of China+2 种基金 Project(20100471021) supported by the China Postdoctoral Science Foundation Project(LBH-Q09134) supported by Heilongjiang Postdoctoral Science-Research Foundation,China Project (HEUFT09013) supported by the Foundation of Harbin Engineering University,China
文摘The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorithm.The command input was corrected by weights to generate the desired input for the algorithm,and the feedback was brought into the feedback correction,whose output was the weighted feedback.The weights of the normalized LMS adaptive filtering algorithm were updated on-line according to the estimation error between the desired input and the weighted feedback.Thus,the updated weights were copied to the input correction.The estimation error was forced to zero by the normalized LMS adaptive filtering algorithm such that the weighted feedback was equal to the desired input,making the feedback track the command.The above concept was used as a basis for the development of amplitude phase control.The method has good real-time performance without estimating the system model.The simulation and experiment results show that the proposed amplitude phase control can efficiently cancel the amplitude attenuation and phase delay with high precision.
