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8th World Congress on Intelligent Control and Automation (WCICA)

作者： Shao Yong Gao Zhiyuan Gao Shouwei Yi Jincong Zhu Xiaojin Shanghai Univ Dept Automat Sch Mechatron Engn & Automat Shanghai Peoples R China

ISBN: (纸本)9781424467129

Taking the piezoelectric flexible beam as the research object, this paper proposed a fxlms algorithm based MIMO adaptive vibration control method to attenuate the oscillations of flexible structures at low frequency. By introducing the piezoelectric constitutive equations and analyzing the multi-channel adaptive filtered feedforward control algorithm and its fxlms algorithm process, the model parameter identification strategy for the controlled structure as well as the controller design structure diagram are given in this paper. Structure modal characteristic analysis was done to determine the optimal configuration of piezoelectric sensors and actuators. Active vibration control experimental platform was established to verify the effectiveness of the fxlms control scheme. The vibration control experiment was done after the control channel model was obtained. The experimental results show that the MIMO adaptive vibration controller proposed in this paper has a good control performance, with low order model and rapid convergence.

关键词： Adaptive Control Active Vibration Control Model Identification fxlms algorithm

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Theoretical convergence analysis of fxlms algorithm

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SIGNAL PROCESSING 2010年第12期90卷 3046-3055页

作者： Ardekani, I. Tabatabaei Abdulla, W. H. Univ Auckland Dept Elect & Comp Engn Auckland 1142 New Zealand

In system identification when a secondary path follows the adaptive filter, the fxlms algorithm is usually applied for updating the adaptive filter. Although several fxlms convergence analyses have been conducted in detail, only a few have intended to derive a convergence condition. In fact, available fxlms convergence conditions are only accurate for simplified cases with pure delay secondary paths or multi-sinusoidal input signals. This paper studies the fxlms convergence behavior for moving average secondary paths and stochastic input signals. A novel model for predicting the fxlms convergence behavior is developed. Based on this model, a necessary and sufficient condition for the convergence of the fxlms is derived. Also, the condition leading to the fastest convergence is proposed. Compared to previously derived convergence conditions, the proposed condition applies to more general secondary paths. Results obtained from this study are found to correspond very well to those obtained from simulation experiments. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Adaptive filters fxlms algorithm Convergence analysis

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Stochastic analysis of fxlms-based internal model control feedback active noise control systems

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SIGNAL PROCESSING 2014年 101卷 121-133页

作者： Wang, Tongwei Gan, Woon-Seng Nanyang Technol Univ Sch Elect & Elect Engn Digital Signal Proc Lab Singapore 63979 Singapore

It is well-known that feedback active noise control (ANC) systems are not able to control stochastic white noise, which is completely unpredictable. However, in practical applications, the undesired primary noise is usually not purely white, but band-limited, and can still be controlled by a feedback ANC system. Nevertheless, theoretical analysis of feedback ANC performance is lacking in the literature, especially for band-limited white noise and imperfect secondary-path modeling. In this paper, a stochastic analysis of a filtered-X least-mean-square (fxlms)-based internal model control (IMC) feedback ANC system is conducted when the primary noise is band-limited white noise. As a result, a mathematical model is developed for the adaptation process in the fxlms-based IMC feedback ANC system, and based on this, a step-size upper bound for maintaining stability and an optimum step size for fastest convergence are derived. Furthermore, it is found that noise bandwidth affects the stability and convergence performance, which is similar to but different than its impact on a feedforward ANC system. Extensive computer simulations are carried out to verify the theoretical analysis results under different noise bandwidths and secondary-path modeling errors. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Adaptive filter Active noise control fxlms algorithm IMC feedback active noise control Step-size upper bound

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A Computationally Efficient Multichannel Active Road Noise Control System

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JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME 2015年第1期137卷 011003-011003页

作者： Duan, Jie Li, Mingfeng Lim, Teik C. Lee, Ming-Ran Cheng, Ming-Te Vanhaaften, Wayne Abe, Takeshi Univ Cincinnati Coll Engn & Appl Sci Vibroacoust & Sound Qual Res Lab Engn Res Ctr 801 Cincinnati OH 45221 USA Ford Motor Co Transmiss Driveline NVH & Adv Technol Dev Dept Dearborn MI 48124 USA

A multichannel active noise control (ANC) system has been developed for a vehicle application, which employs loudspeakers to reduce the low-frequency road noise. Six accelerometers were attached to the vehicle structure to provide the reference signal for the feedforward control strategy, and two loudspeakers and two microphones were applied to attenuate acoustic noise near the headrest of the driver's seat. To avoid large computational burden caused by the conventional time-domain filtered-x least mean square (fxlms) algorithm, a time-frequency domain fxlms (TF-fxlms) algorithm is proposed. The proposed algorithm calculates the gradient estimate and filtered reference signal in the frequency domain to reduce the computational requirement, while also updates the control signals in the time domain to avoid delay. A comprehensive computational complexity analysis is conducted to demonstrate that the proposed algorithm requires significantly lower computational cost as compared to the conventional fxlms algorithm.

关键词： active noise control road noise fxlms algorithm multichannel time-frequency domain computational efficiency

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Adaptive signal processing algorithms for creating spatial zones of quiet

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DIGITAL SIGNAL PROCESSING 2014年第1期27卷 129-139页

作者： Ardekani, Iman Tabatabaei Abdulla, Waleed H. Unitec Inst Technol Auckland New Zealand Univ Auckland Auckland 1 New Zealand

Available adaptive active noise control (ANC) algorithms can only minimize the noise level at a point that an error microphone is placed. Consequently, a zone of quiet around this microphone is produced as a byproduct. However, they cannot technically control or, even, monitor the noise level within the zone of quiet unless they use several sensors. They cannot also control the shape and the extension of the quiet zone by using only the error microphone. This paper develops a signal processing framework for the derivation of adaptive ANC algorithms that can directly create a controllable zone of quiet in monochromatic noise fields using a single error microphone. It is shown that by adding a filter to the standard ANC structure, a controllable zone of quiet is created. The transfer function of this filter is obtained using an accurate mathematical analysis. It is also shown that the extension of the zone of quiet can be controlled by tuning this filter. The implementation of the proposed system requires no additional hardware, rather than those required for traditional ANC systems. The validity of the results are discussed by using numerical analysis. Also, the performance of the proposed system is practically verified. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Adaptive signal processing Active noise control Zone of quiet fxlms algorithm

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Combined Feedforward-Feedback Active Control of Road Noise Inside a Vehicle Cabin

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JOURNAL OF VIBRATION AND ACOUSTICS-TRANSACTIONS OF THE ASME 2014年第4期136卷 041020-1-041020-8页

作者： Duan, Jie Li, Mingfeng Lim, Teik C. Lee, Ming-Ran Cheng, Ming-Te Vanhaaften, Wayne Abe, Takeshi Univ Cincinnati Coll Engn & Appl Sci Vibro Acoust & Sound Qual Res Lab Engn Res Ctr 801 Cincinnati OH 45221 USA Ford Motor Co Res & Adv Engn Ctr Powertrain NVH R&D Dept Dearborn MI 48124 USA

Conventional active control of road noise inside a vehicle cabin generally uses a pure feedforward control system with the conventional filtered-x least mean square (fxlms) algorithm. While it can yield satisfactory noise reduction when the reference signal is well correlated with the targeted noise, in practice, it is not always possible to obtain a reference signal that is highly coherent with a broadband response typically seen in road noise. To address this problem, an active noise control (ANC) system with a combined feedforward-feedback controller is proposed to improve the performance of attenuating road noise. To take full advantage of the feedforward control, a subband (Sfxlms) algorithm, which can achieve more noise attenuation over a broad frequency range, is used to replace the conventional fxlms algorithm. Meanwhile, a feedback controller, based on internal model control (IMC) architecture, is introduced to reduce the road noise components that have strong response but are poorly correlated with the reference signals. The proposed combined feedforward-feedback ANC system has been demonstrated by a simulation model with six reference accelerometers, two control loudspeakers and one error microphone, using actual data measured from a test vehicle. Results show that the performance of the proposed combined controller is significantly better than using either a feedforward controller only or a feedback controller only, and is able to achieve about 4 dBA of overall sound pressure level reduction.

关键词： ANC road noise fxlms algorithm Sfxlms algorithm IMC combined feedforward-feedback

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LMS algorithmIC VARIANTS IN ACTIVE NOISE AND VIBRATION CONTROL 22

LMS ALGORITHMIC VARIANTS IN ACTIVE NOISE AND VIBRATION CONTR...

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22nd European Signal Processing Conference (EUSIPCO)

作者： Rupp, Markus Hausberg, Fabian Vienna Univ Technol Inst Telecommun Gusshausstr 25-389 A-1040 Vienna Austria Audi AG I EF 35 Engine Gearbox Mountings D-85045 Ingolstadt Germany

ISBN: (纸本)9780992862619

In this article we provide analyses of two low complexity LMS algorithmic variants as they typically appear in the context of fxlms for active noise or vibration control in which the reference signal is not obtained by sensors but internally generated by the known engine speed. In particular we show that the algorithm with real valued error is robust and exhibits the same steady state quality as the original complex-valued LMS algorithm but at the expense of only achieving half the learning speed while its counterpart with real-valued regression vector behaves only equivalently in the statistical sense.

关键词： fxlms algorithm error bounds l(2)-stability robustness mean-square-convergence

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Adaptive algorithms for active noise cancellation using time-varying convergence coefficient

Adaptive algorithms for active noise cancellation using time...

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16th International Mechanical Engineering Congress (IMEC)

作者： Bharti, Gaurav Ghangale, Dhananjay Manik, Dhanesh Indian Inst Technol Room 119Hostel 7 Mumbai Maharashtra India Indian Inst Technol Dept Mech Engn Mumbai Maharashtra India

ISBN: (纸本)9783038351634

The performance of an ANC system depends on the convergence factor. A suitable value of convergence coefficient is extremely important as it impacts both the speed of convergence and the stability of the adaptive algorithm. Traditionally, in active noise control systems fixed convergence factor is used. In this paper, a novel approach of time-varying convergence factor mu is used and the results are compared with traditional feedforward and feedback noise control systems. This algorithm leads to faster convergence and provides reduced mean-squared error compared to the conventional fixed parameter algorithm.

关键词： Adaptive algorithm Noise control Acoustics LMS algorithm Filtered-x LMS algorithm fxlms algorithm Noise cancellation convergence parameter step-size parameter

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Feedback active noise control based on forward-backward LMS predictor

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SIGNAL IMAGE AND VIDEO PROCESSING 2013年第6期7卷 1083-1091页

作者： Pavithra, S. Narasimhan, S. V. Natl Inst Technol Karnataka Dept Elect & Commun Engn Surathkal 575025 India Natl Aerosp Labs Aerosp Elect & Syst Div Bangalore 560017 Karnataka India CSIRO New Delhi India

In this paper, a new feedback active noise control (FBANC) system based on forward-backward error LMS (FBLMS) predictor is proposed. The misadjustment of the FBLMS predictor is about half that of the forward error LMS (FLMS) predictor. The new ANC system employs FBLMS predictors both for its main path (MP) predictor and for the noise canceler (NC) for the secondary path (SP) identification (SPI). To realize the MP predictor based on the FBLMS concept, a new fxlms structure is proposed. But for the NC for the SPI, the FBLMS predictor is directly used. The MP predictor based on FBLMS reduces its misadjustment. Further the use of FBLMS predictor for the NC, as it gives a good prediction of primary noise component in the error (residual noise), improves the SNR for SPI. Thus, the improved SP estimate and the reduced misadjustment for the MP predictor achieved result in a significantly better overall noise reduction (of about 8 dB) over the ANC that uses the MP predictor and noise canceler for SPI, both based only on the forward error LMS algorithm. The computational load for the proposed algorithm is about twice that of FBANC that uses only forward error.

关键词： Feedback active noise control Forward-backward tapped delay-line predictor fxlms algorithm

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Stochastic modelling and analysis of filtered-x least-mean-square adaptation algorithm

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IET SIGNAL PROCESSING 2013年第6期7卷 486-496页

作者： Ardekani, Iman Tabatabaei Abdulla, Waleed H. Univ Auckland Dept Elect Engn Auckland 1142 New Zealand

This study represents a stochastic model for the adaptation process performed on adaptive control systems by the filtered-x least-mean-square (fxlms) algorithm. The main distinction of this model is that it is derived without using conventional simplifying assumptions regarding the physical plant to be controlled. This model is then used to derive a set of closed-form mathematical expressions for formulating steady-state performance, stability condition and learning rate of the fxlms adaptation process. These expressions are the most general expressions, which have been proposed so far. It is shown that some previously derived expressions can be obtained from the proposed expressions as special and simplified cases. In addition to computer simulations, different experiments with a real-time control setup confirm the validity of the theoretical findings.

关键词： adaptive control least mean squares methods stability stochastic processes stochastic modelling filtered-x least-mean-square adaptation algorithm adaptation process adaptive control systems fxlms algorithm physical plant closed-form mathematical expressions fxlms adaptation process stability condition steady-state performance computer simulations real-time control setup

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