摘要
为了应对日益严重的噪声污染,有源噪声控制已被公认为与传统无源噪声控制方法相并列的一项技术。然而,随着研究的深入和工程应用范围的扩大,有源噪声控制出现了许多亟待研究和解决的问题。
脉冲噪声的有源控制就是其中之一,已有研究表明,炮弹的爆炸声,鞭炮声,枪支射击声和婴儿恒温箱的噪声等都属于脉冲噪声的范畴,而将常用的基于二阶矩的自适应算法用于脉冲噪声控制,系统就会出现易发散、降噪性能不明显等现象。本文主要针对脉冲噪声有源控制中的自适应算法进行研究,目标是寻求收敛速度快,计算复杂度低,稳态性能好,鲁棒的自适应算法。主要内容及创新点阐述如下：
(1)针对α稳定分布的脉冲噪声的前馈有源控制,定义了一种新的代价函数,即最小化误差绝对值对数变换的平方。在此基础上,提出了滤波对数变换最小均方算法。现有其他算法需要根据实际噪声信号的统计特性预先选择和设定某些参数才能保证算法的收敛和稳定,本文所提出的算法克服了已有算法这方面的局限性。并通过理论和仿真分析对比了所提算法与已有算法的性能。
(2)脉冲声是指含有非期望的、瞬时发生的尖锐声的一类噪声,其时域采样通常表现为尖刺样本或者非常大的离群样本值。为改进脉冲噪声有源控制的稳定性,借鉴鲁棒性统计理论中的M估计器概念,提出了一类基于M估计器的自适应算法,并将现有多种算法归入基于M估计器算法族中。通过理论和仿真分析对比了所提算法与已有算法的性能。
(3)提出了一种后滤波结构的自适应算法。该算法的代价函数是一个约束优化问题：在满足后验误差为零的约束条件下,使得当前待更新的滤波器系数矢量与过去所有滤波器系数矢量之间差的欧几里得范数加权平方和最小。采用拉格朗日数乘法求解该约束优化问题,得到该算法是归一化滤波最小均方算法的泛化形式,即将归一化滤波最小均方算法得到的滤波器系数通过一个一阶的无限脉冲响应滤波器。通过调节无限脉冲响应滤波器的极点位置,可以控制自适应算法的收敛速度,稳态误差及稳定性。理论分析和仿真验证了该算法的有效性。另一方面,后滤波规整最小均方算法的优化准则是直接对滤波器系数的范数加以控制,即保证每次迭代中,滤波器系数矢量的变化都尽可能的小,因此将该算法用于脉冲噪声的有源控制。此外,以实际的打桩机噪声有源控制为例,比较了已有的脉冲噪声控制算法的性能,给出了选择合适的自适应算法的过程。
(4)内模型控制是自适应反馈有源噪声控制中常用的系统结构,该结构通过合成参考信号的方式将反馈系统转换成前馈系统,从而可以方便地将前馈自适应算法应用到反馈系统中。该方法中的参考信号是由误差信号与次级信号经过估计的次级路径滤波后的信号合成得到的。理想情况下,当次级路径的估计无误差时,该系统具有较好的性能。但是其计算量较大,特别是次级信号与估计的次级路径的滤波操作。从反馈有源噪声控制系统的实际情况出发,提出了一种简化的自适应反馈有源噪声控制系统,该系统将误差信号直接用作参考信号,从而省去了次级信号与估计的次级路径的滤波操作。理论分析和实验表明该简化系统的性能并没有明显的恶化,因而是可行的。
Active noise control (ANC), ranking with the passive noise control, is a well-known approach to solve the problem of noise pollution in the environments. After the tireless efforts of researchers for decades, ANC system, especially the adaptive ANC system achieves many concrete and encouraging progresses and the theoretical framework and research method of ANC have been established. However, with the developments of research and the scope of engineering applications, some difficulties are encountered and there are many urgent issues in need of study and solution.
The adaptive algorithms in the adaptive ANC system are investigated in this dissertation and the target is to seek the algorithms which have fast convergence speed, low computation complexity, good steady-state performance and robustness for the practical ANC system. The main contributions of this dissertation are summarized as follows:
For the adaptive feed-forward control of a stable distribution noises, the cost function which is defined as the logarithmic transformation square of error signal is introduced and the FxlogLMS algorithm is derived. The FxlogLMS algorithm does not require any prior knowledge or estimation of characteristic exponent and exhibits good stability for all the cases with different characteristic exponents. Numerical simulations demonstrate the effectiveness of the proposed algorithm.
The M-Estimator based algorithm family is examined in the context of active impulse-like noise control, where several existing algorithms are reformulated into the algorithm family and two new members, i.e. the Fair and Cauchy algorithms, are proposed. The general characteristics of the algorithm family in terms of robustness and computation load are analyzed, and the convergence condition of the proposed new algorithms is developed mathematically. Simulations are performed to verify the effectiveness of the algorithms and it is shown that the proposed algorithms compare favorably with the competitor algorithm in terms of performance, complexity, and threshold selection, and the Cauchy algorithm exhibits better performance under a stable distribution noise condition.
An improved algorithm named PFNLMS is proposed which features that the filter coefficients are processed by a post filter and then utilized for adaptation. It is shown that the PFNLMS algorithm exhibits inherent flexibility since it can balance the convergence speed and steady state performance by tuning the parameter in the post filter. Because the cost function of the PFNLMS algorithm is defined as the summation of the squared Euclidean norm of difference between the currently updated filter coefficients vector and all past filter coefficients vector subject to the constraint imposed on the adaptive filter output, The PFNLMS algorithm is very suitable for the active control of impulsive noise since it directly limits the dynamic range of the adaptive filter coefficients and prevents the heavy fluctuation of the filter coefficients. Simulations compare the performance of the proposed algorithm with the existing algorithms. In addition, a procedure of selecting an appropriate algorithm from the family for practical applications is illustrated by simulations of active control of recorded pile driving noise.
The widely used adaptive feedback active noise control system is based on the internal model control (IMC) structure where the reference signal is regenerated by synthesizing the error signal and the secondary signal filtered with the estimation of the secondary path. A simplified adaptive feedback active noise control system which uses the error signal directly as the reference signal is presented and the advantages of the simplified adaptive feedback active noise control system are the low computational load and ease of implementation. The convergence and stability is investigated and the common observations in practical active noise control system support that the simplification is reasonable. The simulations and experiments of active noise control system in a long duct for narrow band noise suppression show that the performance of the simplified adaptive feedback active noise control system is comparable to that of the adaptive IMC feedback system.
引文
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