A Simplified Method for Online Secondary Path Modeling in Multichannel ANC Systems

Proceedings of IEEE International Midwest Symposium on Circuits and System

Performance analysis and design of FxLMS algorithm in broadband ANC system with online secondary-path modeling

The filtered-x LMS (FxLMS) algorithm has been widely used in active noise control (ANC) systems, where the secondary path is usually estimated online by injecting auxiliary noises. In such an ANC system, the ANC controller and the secondary-path estimator are coupled with each other, which make it difficult to analyze the performance of the entire system. Therefore, a comprehensive performance analysis of broadband ANC systems is not available currently to our best knowledge. In this paper, the convergence behavior of the FxLMS algorithm in broadband ANC systems with online secondary-path modeling is studied. Difference equations which describe the mean and mean square convergence behaviors of the adaptive algorithms are derived. Using these difference equations, the stability of the system is analyzed. Finally, the coupled equations at the steady state are solved to obtain the steady-state excess mean square errors (EMSEs) for the ANC controller and the secondary-path estimator. Computer simulations are conducted to verify the agreement between the simulated and theoretically predicted results. Moreover, using the proposed theoretical analysis, a systematic and simple design procedure for ANC systems is proposed. The usefulness of the theoretical results and design procedure is demonstrated by means of a design example. © 2012 IEEE.published_or_final_versio

Spatial Noise-Field Control With Online Secondary Path Modeling: A Wave-Domain Approach

Due to strong interchannel interference in multichannel active noise control (ANC), there are fundamental problems associated with the filter adaptation and online secondary path modeling remains a major challenge. This paper proposes a wave-domain adaptation algorithm for multichannel ANC with online secondary path modelling to cancel tonal noise over an extended region of two-dimensional plane in a reverberant room. The design is based on exploiting the diagonal-dominance property of the secondary path in the wave domain. The proposed wave-domain secondary path model is applicable to both concentric and nonconcentric circular loudspeakers and microphone array placement, and is also robust against array positioning errors. Normalized least mean squares-type algorithms are adopted for adaptive feedback control. Computational complexity is analyzed and compared with the conventional time-domain and frequency-domain multichannel ANCs. Through simulation-based verification in comparison with existing methods, the proposed algorithm demonstrates more efficient adaptation with low-level auxiliary noise.DP14010341

Doctor of Philosophy

dissertationThe dissertation is concerned with the development and analysis of adaptive algorithms for the rejection of unknown periodic disturbances acting on an unknown system. The rejection of periodic disturbances is a problem frequently encountered in control engineering, and in active noise and vibration control in particular. A new adaptive algorithm is presented for situations where the plant is unknown and may be time-varying. Known as the adaptive harmonic steady-state or ADHSS algorithm, the approach consists in obtaining on-line estimates of the plant frequency response and of the disturbance parameters. The estimates are used to continuously update control parameters and cancel or minimize the effect of the disturbance. The dynamic behavior of the algorithm is analyzed using averaging theory. Averaging theory allows the nonlinear time-varying closed-loop system to be approximated by a nonlinear time-invariant system. Extensions of the algorithm to systems with multiple inputs/outputs and disturbances consisting of multiple frequency components are provided. After considering the rejection of sinusoidal disturbances of known frequency, the rejection of disturbances of unknown frequency acting on an unknown and time-varying plant is considered. This involves the addition of frequency estimation to the ADHSS algorithm. It is shown that when magnitude phase-locked loop (MPLL) frequency estimation is integrated with the ADHSS algorithm, the two components work together in such a way that the control input does not prevent frequency tracking by the frequency estimator and so that the order of the ADHSS can be reduced. While MPLL frequency estimation can be combined favorably with ADHSS disturbance rejection, stability is limited due to the local convergence properties of the MPLL. Thus, a new frequency estimation algorithm with semiglobal stability properties is introduced. Based on the theory of asynchronous electric machines, the induction motor frequency estimator, or IMFE, is shown to be appropriate for disturbance cancellation and, with modification, is shown to increase stability of the combined ADHSS/MPLL algorithm. Extensive active noise control experiments demonstrate the performance of the algorithms presented in the dissertation when disturbance and plant parameters are changing

DISCRETE-TIME ADAPTIVE CONTROL ALGORITHMS FOR REJECTION OF SINUSOIDAL DISTURBANCES

We present new adaptive control algorithms that address the problem of rejecting sinusoids with known frequencies that act on an unknown asymptotically stable linear time-invariant system. To achieve asymptotic disturbance rejection, adaptive control algorithms of this dissertation rely on limited or no system model information. These algorithms are developed in discrete time, meaning that the control computations use sampled-data measurements. We demonstrate the effectiveness of algorithms via analysis, numerical simulations, and experimental testings. We also present extensions to these algorithms that address systems with decentralized control architecture and systems subject to disturbances with unknown frequencies

ANCシステムにおけるオンライン2次経路とフィードバック経路モデリングのための補助ノイズ電力スケジューリングに関する研究

The idea of cancelling the acoustic noise by generating an anti-noise signal is very fascinating, and was first proposed by P. Lueg in 1936. In feedforward active noise control (ANC) systems, the anti-noise signal is generated with the help of reference and error microphones, an adaptive filtered-x-LMS (FxLMS) algorithm based ANC filter, and an electro-acoustic path named as the secondary path. For stable operation of ANC systems, the FxLMS algorithm needs an estimate of the secondary path. The anti-noise signal generated by the loudspeaker (part of secondary path) causes interference with the reference microphone signal. This interference is due to the presence of electro-acoustic path, named as feedback path, between the loudspeaker and the reference microphone. It is required to neutralize the effect of this feedback path, and hence an estimate of the feedback path is required. For online modeling of the secondary and feedback paths, an additional auxiliary noise is injected. This auxiliary noise contributes to the residual error, and thus degrades the noise-reduction-performance (NRP) of ANC system. In order to improve the NRP, a gain scheduling strategy is used to vary the variance of the injected auxiliary noise. The purpose of the gain scheduling is that when the model estimates of the secondary and the feedback paths are far from the actual unknown paths, auxiliary noise with large variance is injected. Once the model estimates are closer to the actual unknown paths, the variance of auxiliary noise is reduced to a small value. In this way, on one hand the gain scheduling can help us to achieve the required model estimates of secondary and feedback paths, and on the other hand to improve the NRP at the steady-state. In this thesis, we discuss the two most important issues, i.e., 1) online secondary path modeling (OSPM), and 2) online feedback path modeling and neutralization (FBPMN) with gain scheduling. In chapter 1, the basic underlying physical principle and configurations of active noise control (ANC) systems are explained. The application of the basic building block of an ANC system i.e. An adaptive filter, in different system identification scenarios is discussed. The most popular adaptive algorithm for ANC system, i.e., FxLMS algorithm is derived for the general secondary path. A brief overview is given for the two fundamental issues in ANC systems, i.e., 1) OSPM and 2) online FBPMN. The use of optimal excitation signal, i.e., Perfect sweep signals for system identification is described. In chapter 2, the existing methods for OSPM without gain scheduling, where the auxiliary noise with fixed variance is used in all operating conditions, are discussed. In this chapter a simplified structure for OSPM with the modified FxLMS (MFxLMS) adaptive algorithm is proposed. The advantage of the simplified structure is that it reduces the computational complexity of the MFxLMS algorithm based OSPM without having any compromise on the performance of ANC system. In chapter 3, the existing methods for OSPM with gain scheduling are discussed. The drawbacks with the existing gain scheduling strategies are highlighted, and some new gain scheduling strategies are proposed to improve the modeling accuracy of SPM filter and the NRP of an ANC system. In existing methods, the gain is varied based on the power of residual error signal which carries information only about the convergence status of ANC system. In the Proposed methods the gain is varied based on the power of error signal of SPM filter. This is more desirable way of controlling the gain because the power of error signal of SPM filter carries information about the convergence status of both the ANC system and the SPM filter. The performance comparison is carried out through the simulation results. In chapter 4, the second most important issue associated with the feedforward configuration of ANC system, i.e., the issue of online FBPMN is deal with. In the first part, the existing methods for online FBPMN without gain scheduling are discussed. A new structure is proposed for online FBPMN without gain scheduling. The performance of the existing methods is compare with the proposed method through the simulation results. In the new structure the good features from the existing structures are combined together. The predictor is used in the new structure to remove the predictable interference term from the error signal of adaptive FBPMN filter. In addition to this, the action of FBPM filter and the FBPN filter is combined into a single FBPMN filter. The advantage of the new structure over the existing structures is that it can better neutralize the effect of feedback coupling on the input signal of ANC filter, thus improves the convergence of ANC system. In the second part, a gain scheduling strategy is proposed to improve the NRP of ANC system. In addition to this, a self-tuned ANP scheduling strategy with matching step-size for FBPMN filter is also proposed that requires no tuning parameters and further improves the NRP of ANC systems. In chapter 5, the concluding remarks and some future research directions are given.電気通信大学201