Active Noise Control with Sampled-Data Filtered-x Adaptive Algorithm

Analysis and design of filtered-x adaptive algorithms are conventionally done by assuming that the transfer function in the secondary path is a discrete-time system. However, in real systems such as active noise control, the secondary path is a continuous-time system. Therefore, such a system should be analyzed and designed as a hybrid system including discrete- and continuous- time systems and AD/DA devices. In this article, we propose a hybrid design taking account of continuous-time behavior of the secondary path via lifting (continuous-time polyphase decomposition) technique in sampled-data control theory

Modified filtered-x hierarchical lms algorithm with sequential partial updates for active noise control

In the field of active noise control (ANC), a popular method is the modified filtered-x LMS algorithm. However, it has two drawbacks: Its computational complexity higher than that of the conventional FxLMS, and its convergence rate that could still be improved. Therefore, we propose an adaptive strategy which aims at speeding up the convergence rate of an ANC system dealing with periodic disturbances. This algorithm consists in combining the organization of the filter weights in a hierarchy of subfilters of shorter length and their sequential partial updates (PU). Our contribution is threefold: (1) we provide the theoretical basis of the existence of a frequency-depend-ent parameter, called gain in step-size. (2) The theoretical upper bound of the step-size is compared with the limit obtained from simulations. (3) Additional experiments show that this strategy results in a fast algorithm with a computational complexity close to that of the conventional FxLMS

Estimation-based synthesis of H∞-optimal adaptive FIR filtersfor filtered-LMS problems

This paper presents a systematic synthesis procedure for H∞-optimal adaptive FIR filters in the context of an active noise cancellation (ANC) problem. An estimation interpretation of the adaptive control problem is introduced first. Based on this interpretation, an H∞ estimation problem is formulated, and its finite horizon prediction (filtering) solution is discussed. The solution minimizes the maximum energy gain from the disturbances to the predicted (filtered) estimation error and serves as the adaptation criterion for the weight vector in the adaptive FIR filter. We refer to this adaptation scheme as estimation-based adaptive filtering (EBAF). We show that the steady-state gain vector in the EBAF algorithm approaches that of the classical (normalized) filtered-X LMS algorithm. The error terms, however, are shown to be different. Thus, these classical algorithms can be considered to be approximations of our algorithm. We examine the performance of the proposed EBAF algorithm (both experimentally and in simulation) in an active noise cancellation problem of a one-dimensional (1-D) acoustic duct for both narrowband and broadband cases. Comparisons to the results from a conventional filtered-LMS (FxLMS) algorithm show faster convergence without compromising steady-state performance and/or robustness of the algorithm to feedback contamination of the reference signal

Reduksi Noise Akustik Secara Aktif Dengan Metode Filtered-X Least Mean Square

The paper describes an implementation of an active noice canceller by using the algorithm of Filtered-X Least Mean Square (Filtered-X LMS). The system was implemented on a digital signal processor starter kit of TMS 320C50. The system was equipped with 2 speakers as sound source and noise source and microphones as sound sensors. The processor controlled the noise by generating an anti-noise sound trying to cancelled the noise so that the total noise would be reduced. The experimental results shows the system could reduce noise with the level of 20 dBV

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

Adaptive Filtering with Bandwidth Constraints in the Feedback Path

Abstract This paper introduces a new, adaptive-filter-based controller that shows advantageous properties from the viewpoint of its communication requirement. The algorithm is called signed-error filtered-x LMS (SE-FxLMS). Its novelty is characterized by the fact that it makes possible data compression in the feedback path of adaptive-filter-based control loops in a very simple way. This feature is especially useful in such closed-loop systems where the feedback signals are transmitted over a low-bandwidth communication channel. This is a typical case in so-called networked control systems (NCS) where the communication is carried out over a shared communication channel, e.g., using a wireless sensor network. The paper introduces an analysis of the algorithm as well

Desenvolvimento de uma plataforma experimental de baixo custo para implementação de controle ativo de ruído em dutos acústicos / Development of a low-cost experimental platform for implementing active noise control in acoustic ducts

Atualmente o desenvolvimento de sistemas de controle ativo de ruído tem recebido considerável interesse da área científica, pois a poluição sonora tem influência direta sobre o meio ambiente e sobre a qualidade de vida dos seres humanos. Neste contexto, o desenvolvimento de plataformas experimentais que permitam a rápida implementação e avaliação de algoritmos de controle ativo de ruído é fundamental. Desta forma, este artigo irá apresentar todas as etapas envolvidas no projeto e construção de uma plataforma experimental de baixo custo, desde a sua ideia conceitual, passando pelas etapas de construção da estrutura física, instrumentação e desenvolvimento do sistema de aquisição de dados. A ideia principal é que esta bancada permita a implementação, avaliação e comparação de diferentes algoritmos de controle, verificando o desempenho e características de cada um deles no que diz respeito ao nível de atenuação alcançado na saída do sistema. Adicionalmente, a bancada pode permitir o estudo de diversos temas específicos, tais como análise modal, identificação de sistemas, isolamento acústico entre outros. Este artigo aborda ainda o problema de identificação experimental do modelo matemático que descreve o comportamento dinâmico do sistema. A validação experimental da plataforma é realizada através da implementação de duas técnicas de controle muito comuns na literatura conhecidas como algoritmo Least Mean Square (LMS) e o algoritmo Filtered x LMS (FxLMS)