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A computationally efficient adaptive IIR solution to active noise and vibration control systems

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A computationally efficient adaptive IIR solution to active noise and vibration control systems. / Montazeri, Allahyar; Poshtan, Javad.
In: IEEE Transactions on Automatic Control, Vol. 55, No. 11, 11.2010, p. 2671-2676.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Montazeri, A & Poshtan, J 2010, 'A computationally efficient adaptive IIR solution to active noise and vibration control systems', IEEE Transactions on Automatic Control, vol. 55, no. 11, pp. 2671-2676. https://doi.org/10.1109/TAC.2010.2067670

APA

Montazeri, A., & Poshtan, J. (2010). A computationally efficient adaptive IIR solution to active noise and vibration control systems. IEEE Transactions on Automatic Control, 55(11), 2671-2676. https://doi.org/10.1109/TAC.2010.2067670

Vancouver

Montazeri A, Poshtan J. A computationally efficient adaptive IIR solution to active noise and vibration control systems. IEEE Transactions on Automatic Control. 2010 Nov;55(11):2671-2676. doi: 10.1109/TAC.2010.2067670

Author

Montazeri, Allahyar ; Poshtan, Javad. / A computationally efficient adaptive IIR solution to active noise and vibration control systems. In: IEEE Transactions on Automatic Control. 2010 ; Vol. 55, No. 11. pp. 2671-2676.

Bibtex

@article{171ccc05ecff4943b13e48542a98ab39,
title = "A computationally efficient adaptive IIR solution to active noise and vibration control systems",
abstract = "In spite of special advantages of IIR filters in active noise and vibration control (ANVC) applications, the multimodal error surface and instability problem of adaptive IIR filters has prevented its extensive use. To alleviate these problems, in this paper, a new RLS-based fast array adaptive IIR filters in ANVC applications is proposed. The algorithm is developed with slow adaptation assumption and by transforming the active noise and vibration control problem to an output-error identification problem. By derivation of the fast-array equivalent form both computational complexity and numerical stability of the proposed algorithm are improved. The geometrical illustration of the algorithm, in a simple case, is also given to unify and complete its mathematical formulation. In spite of low computational complexity of the order O(n), simulation results confirm high convergence speed of the proposed algorithm and also its ability to reach the lower minimum mean square error in comparison with commonly used adaptive IIR algorithms in ANVC systems.",
keywords = "IIR digital filter stability, Adaptive filters, CONVERGENCE ANALYSIS, noise and vibration control, ALGORITHM, FILTER",
author = "Allahyar Montazeri and Javad Poshtan",
year = "2010",
month = nov,
doi = "10.1109/TAC.2010.2067670",
language = "English",
volume = "55",
pages = "2671--2676",
journal = "IEEE Transactions on Automatic Control",
issn = "0018-9286",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "11",

}

RIS

TY - JOUR

T1 - A computationally efficient adaptive IIR solution to active noise and vibration control systems

AU - Montazeri, Allahyar

AU - Poshtan, Javad

PY - 2010/11

Y1 - 2010/11

N2 - In spite of special advantages of IIR filters in active noise and vibration control (ANVC) applications, the multimodal error surface and instability problem of adaptive IIR filters has prevented its extensive use. To alleviate these problems, in this paper, a new RLS-based fast array adaptive IIR filters in ANVC applications is proposed. The algorithm is developed with slow adaptation assumption and by transforming the active noise and vibration control problem to an output-error identification problem. By derivation of the fast-array equivalent form both computational complexity and numerical stability of the proposed algorithm are improved. The geometrical illustration of the algorithm, in a simple case, is also given to unify and complete its mathematical formulation. In spite of low computational complexity of the order O(n), simulation results confirm high convergence speed of the proposed algorithm and also its ability to reach the lower minimum mean square error in comparison with commonly used adaptive IIR algorithms in ANVC systems.

AB - In spite of special advantages of IIR filters in active noise and vibration control (ANVC) applications, the multimodal error surface and instability problem of adaptive IIR filters has prevented its extensive use. To alleviate these problems, in this paper, a new RLS-based fast array adaptive IIR filters in ANVC applications is proposed. The algorithm is developed with slow adaptation assumption and by transforming the active noise and vibration control problem to an output-error identification problem. By derivation of the fast-array equivalent form both computational complexity and numerical stability of the proposed algorithm are improved. The geometrical illustration of the algorithm, in a simple case, is also given to unify and complete its mathematical formulation. In spite of low computational complexity of the order O(n), simulation results confirm high convergence speed of the proposed algorithm and also its ability to reach the lower minimum mean square error in comparison with commonly used adaptive IIR algorithms in ANVC systems.

KW - IIR digital filter stability

KW - Adaptive filters

KW - CONVERGENCE ANALYSIS

KW - noise and vibration control

KW - ALGORITHM

KW - FILTER

U2 - 10.1109/TAC.2010.2067670

DO - 10.1109/TAC.2010.2067670

M3 - Journal article

VL - 55

SP - 2671

EP - 2676

JO - IEEE Transactions on Automatic Control

JF - IEEE Transactions on Automatic Control

SN - 0018-9286

IS - 11

ER -