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Multivariable control of tonal disturbances using minimization of the maximum error signal through adaptive error signal weighting

机译:通过自适应误差信号加权最小化最大误差信号,对音调扰动进行多变量控制

摘要

In many multichannel active noise and vibration control systems the controller is adapted to minimize the 2-norm of the error signals. This may, however, lead to a large spatial variance in the residual error. A method of achieving a more uniformly controlled error field using a weighted squared error strategy has previously been proposed, although the presented method of defining the error weighting parameters results in a very slow convergence rate. This convergence rate limitation has been overcome by the minimax algorithm which minimizes, in a least-squares sense, the maximum error signal at each iteration. However, due to the inherent switching in this algorithm, for fast convergence speeds it suffers from significant misadjustment and in a tonal control problem this introduces additional unwanted spectral components. In this paper an alternative method of minimizing the maximum error signal is proposed which uses an adaptive error-weighting matrix that is bounded and so avoids the slow convergence speeds previously reported. It is also shown that the proposed algorithm does not suffer from the same misadjustement problems shown by the minimax algorithm. The details of the proposed method are first outlined and then its performance is compared to the previously proposed methods through a series of time-domain simulations employing measurements of a physical system.
机译:在许多多通道有源噪声和振动控制系统中,控制器适用于最小化误差信号的2范数。但是,这可能会导致残留误差的较大空间差异。尽管提出的定义误差加权参数的方法会导致非常慢的收敛速度,但是先前已经提出了使用加权平方误差策略获得更均匀控制的误差场的方法。这种收敛速率限制已由minimax算法克服,该算法在最小二乘意义上最小化了每次迭代时的最大误差信号。然而,由于该算法的固有切换,对于快速收敛速度,它会遭受重大的失调,并且在音调控制问题中,这会引入其他不必要的频谱分量。本文提出了一种最小化最大误差信号的替代方法,该方法使用有界的自适应误差加权矩阵,从而避免了先前报道的收敛速度慢。还表明,所提出的算法不会遭受与minimax算法所示的相同的失调问题。首先概述提出的方法的细节,然后通过一系列使用物理系统测量的时域模拟将其性能与先前提出的方法进行比较。

著录项

  • 作者

    Cheer Jordan; Daley Stephen;

  • 作者单位
  • 年度 2014
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
  • 中图分类

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