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基于FxKalman算法的有源控制器设计与实现研究

发布时间:2019-01-12 16:37
【摘要】:近年来,对于有源噪声控制算法的性能越来越重视。与基于维纳滤波原理的最小均方滤波(Filtered-x Least Mean Square,Fx LMS)、最小二乘滤波(Filtered-x Recursive Least Square,Fx RLS)算法相比较,基于卡尔曼滤波的有源控制算法(Filtered-x Kalman,Fx Kalman)具有较快的收敛速度和良好的跟踪性能,且对带宽噪声有较好的降噪性能。设计、仿真运行了Fx Kalman算法的有源控制器,并针对单频、窄带和宽带信号,在实验室封闭空间对Fx Kalman算法、Fx LMS算法和Fx RLS算法进行有源控制器验证性实验比较,证实了Fx Kalman有源控制器具有上述优点。而如果初级噪声为单频信号且对算法收敛速度要求不高,Fx LMS算法是最经济稳妥的选择。当需要控制带宽噪声或对算法收敛速度要求较高时,Fx Kalman算法则为最好的选择。
[Abstract]:In recent years, more and more attention has been paid to the performance of active noise control algorithms. Compared with the least mean square filter (Filtered-x Recursive Least Square,Fx RLS) algorithm based on Wiener filter principle, the active control algorithm based on Kalman filter (Filtered-x Kalman,) is compared with the least square filter (Filtered-x Recursive Least Square,Fx RLS) algorithm. Fx Kalman) has fast convergence speed, good tracking performance and good noise reduction performance for bandwidth noise. The active controller of Fx Kalman algorithm is designed and simulated. For single frequency, narrow band and wideband signals, the verification experiments of Fx Kalman algorithm, Fx LMS algorithm and Fx RLS algorithm are carried out in laboratory closed space. It is proved that the Fx Kalman active controller has the above advantages. However, if the primary noise is a single frequency signal and the convergence speed of the algorithm is not high, the, Fx LMS algorithm is the most economical and safe choice. , Fx Kalman algorithm is the best choice when the bandwidth noise control is needed or the convergence speed of the algorithm is high.
【作者单位】: 杭州应用声学研究所;
【分类号】:TB535


本文编号:2407986


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