Skip to main content
SpringerLink
Log in

An improved stability compensation for feedforward active noise control systems with acoustic feedback

  • Original Article
  • Published:
Journal of Mechanical Science and Technology Aims and scope Submit manuscript

Abstract

The feedforward active noise control (ANC) methods have been reported as a suitable option to achieve the attenuation of broadband noise. However, many feedforward control systems suffer from the acoustic feedback problem, which affects the reliability of the reference signal measurement and can potentially destabilize the system. In this paper, a Youla parameterized feedforward control strategy is proposed, which guarantees the stability requirement of the control loop in the presence of the acoustic feedback phenomenon. Moreover, it is known that the attenuation of broadband noise requires a large number of adaptive adjustable parameters in the finite impulse response (FIR) type feedforward ANC systems, which directly increases the computational burden. We propose an infinite impulse response (IIR) type adaptive algorithm for the parameterized control system reducing the adjustable parameters. Lastly, a duct noise attenuation experimental system with acoustic feedback is used to verify the proposed improved adaptive feedforward ANC algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Abbreviations

ANC :

Active noise control

SPR :

Strictly positive real

FIR :

Finite impulse response

IIR :

Infinite impulse response

RLS :

Recursive least squares

LMS :

Least mean square

θ :

Youla parameter vector

ϕ r(k):

Regressive vector in RLS or LMS algorithm

P r(k):

Adaptive gain matrix in RLS algorithm

μ :

Step size in LMS algorithm

References

  1. C. Hansen, S. Snyder, X. Qiu, L. Brooks and D. Moreau, Active Control of Noise and Vibration, CRC Press, London, UK (2012).

    Google Scholar 

  2. L. Lu, K.-L. Yin, R. C. de Lamare, Z. Zheng, Y. Yu, X. Yang and B. Chen, A survey on active noise control in the past decade—part I: linear systems, Signal Processing, 183 (2021) 108039.

    Article  Google Scholar 

  3. S. Skogestad and I. Postlethwaite, Multivariable Feedback Control: Analysis and Design, John Wiley & Sons, Inc, Hoboken (2005).

    Google Scholar 

  4. D. Shi, W. S. Gan, B. Lam and S. Wen, Feedforward selective fixed-filter active noise control: algorithm and implementation, IEEE/ACM Transactions on Audio, Speech, and Language Processing, 28 (2020) 1479–1492.

    Google Scholar 

  5. J.-M. Ku, W.-B. Jeong and C. Hong, Controller design for active noise control of compressor by using the time window POCS technique, Journal of Mechanical Science and Technology, 34(7) (2020) 2693–2700.

    Article  Google Scholar 

  6. B. Widrow, D. Shur and S. Shaffer, On adaptive inverse control, Proceeding of the 15th Asilomar Conference on Circuits, Systems and Computers, Pacific Grove, CA, USA (1981) 185–189.

  7. H. Meng and S. Chen, A modified adaptive weight-constrained FxLMS algorithm for feedforward active noise control systems, Applied Acoustics, 164 (2020) 107227.

    Article  Google Scholar 

  8. F. Yang, J. Guo and J. Yang, Stochastic analysis of the filtered-x LMS algorithm for active noise control, IEEE/ACM Transactions on Audio, Speech, and Language Processing, 28 (2020) 2252–2266.

    Article  Google Scholar 

  9. S. Im, S. Kim, S. Woo, I. Jang, T. Han, U. Hwang, W.-S. Ohm and M. Lee, Deep learning-assisted active noise control in a time-varying environment, Journal of Mechanical Science and Technology, 37(3) (2023) 1189–1196.

    Article  Google Scholar 

  10. M. Tufail, S. Ahmed, M. Rehan and M. T. Akhtar, A two adaptive filters-based method for reducing effects of acoustic feedback in single-channel feedforward ANC systems, Digital Signal Processing, 90 (2019) 18–27.

    Article  MathSciNet  Google Scholar 

  11. T. J. Sutton, S. J. Elliott, A. M. Mcdonald and T. J. Saunders, Active control of road noise inside vehicles, Noise Control Engineering Journal, 42(4) (1990) 137–147.

    Article  Google Scholar 

  12. H. Sano, S. Adachi and H. Kasuya, Application of a least squares lattice algorithm to active noise control for an automobile, Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, 119(2) (1997) 318–320.

    Article  Google Scholar 

  13. S. M. Kuo and D. R. Morgan, Active noise control: A tutorial review, Proceedings of the IEEE, 87(6) (1999) 943–973.

    Article  Google Scholar 

  14. L. J. Eriksson, M. C. Allie and R. A. Greiner, The selection and application of an IIR adaptive filter for use in active sound attenuation, IEEE Transactions on Acoustics, Speech, Signal Processing, 35(4) (1987) 433–437.

    Article  Google Scholar 

  15. A. K. Wang and W. Ren, Convergence analysis of the filtered-U algorithm for active noise control, Signal Processing, 73(3) (1999) 255–266.

    Article  Google Scholar 

  16. C. Mosquera and F. Perez-Gonzalez, Convergence analysis of the multiple-channel filtered-U recursive LMS algorithm for active noise control, Signal Processing, 80(5) (2000) 849–856.

    Article  Google Scholar 

  17. R. Fraanje, M. Verhaegen and N. Doelman, Convergence analysis of the filtered-U LMS algorithm for active noise control in case perfect cancellation is not possible, Signal Processing, 83(6) (2003) 1239–1254.

    Article  Google Scholar 

  18. H.-W. Kim, H.-S. Park, S.-K. Lee and K. Shin, Modified-filtered-u LMS algorithm for active noise control and its application to a short acoustic duct, Mechanical Systems and Signal Processing, 25(1) (2011) 475–484.

    Article  ADS  Google Scholar 

  19. I. D. Landau, R. Melendez, T.-B. Airimitoaie and L. Dugard, Beyond the delay barrier in adaptive feedforward active noise control using Youla-Kucera parametrization, Journal of Sound and Vibration, 455 (2019) 339–358.

    Article  ADS  Google Scholar 

  20. F. Li, Z. Wu, F. Qian, T. Yue and T. Xu, Adaptive active noise feedforward compensation for exhaust ducts using a FIR Youla parametrization, Mechanical Systems and Signal Processing, 170 (2022) 108803.

    Article  Google Scholar 

  21. I. Mahtout, F. Navas, V. Milanes and F. Nashashibi, Advances in youla-kucera parametrization: A review, Annual Reviews in Control, 49 (2020) 81–94.

    Article  MathSciNet  Google Scholar 

  22. W. Z. Zhu, L. Luo, M. G. Christensen and J. W. Sun, A new feedforward hybrid active control system for attenuating multi-frequency noise with bursty interference, Mechanical Systems and Signal Processing, 144 (2020) 106859.

    Article  Google Scholar 

  23. Y. Jiang, S. M. Chen, F. H. Gu, H. Meng and Y. T. Cao, A modified feedforward hybrid active noise control system for vehicle, Applied Acoustics, 175 (2021) 107816.

    Article  Google Scholar 

  24. T. Chen and B. A. Francis, Optimal Sampled-Data Control Systems, Springer, London, UK (1995).

    Book  Google Scholar 

  25. I. D. Landau, R. Lozano, M. Msaad and A. Karimi, Adaptive Control: Algorithms, Analysis and Applications, Springer, London, UK (2011).

    Book  Google Scholar 

  26. G. C. Goodwin and K. S. Sin, Adaptive Filtering Prediction and Control, Prentice-Hall, Englewood Cliffs (1984).

    Google Scholar 

  27. T. Padhi, M. Chandra, A. Kar and M. N. S. Swamy, Design and analysis of an improved hybrid active noise control system, Applied Acoustics, 127 (2017) 260–269.

    Article  Google Scholar 

Download references

Acknowledgments

This work is supported by the National Natural Science Foundation of China (52075315, 51675321).

Author information

Authors and Affiliations

  1. Department of Precision Mechanical Engineering, Shanghai University, Shanghai, 200444, China

    Feng Li, Haichun Ding, Zhizheng Wu & Tianqi Liu

  2. Department of Mechanical Electronics, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Fanfan Qian

  3. Dunlap Institute for Astronomy and Astrophysics, University of Toronto, Toronto, M5S 3H4, Canada

    Azhar Iqbal

Authors
  1. Feng Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Haichun Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhizheng Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fanfan Qian
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tianqi Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Azhar Iqbal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhizheng Wu.

Additional information

Feng Li received the B.S. degree and M.S. degree from Anhui University of Technology, China, in 2013 and 2016. He is currently pursuing a Ph.D. degree at the Department of Precision Mechanical Engineering, Shanghai University, China. His research interests include adaptive active vibration control and active noise control.

Haichun Ding received the B.S. degree from Huaiyin Institute of Technology, China, in 2016, and M.S. degree from Dalian Jiaotong University, China, in 2019. He is currently working toward the Ph.D. degree at the Department of Precision Mechanical Engineering, Shanghai University, China. His current research interests include optomechatronic system, adaptive optics and vibration control.

Zhizheng Wu is a Professor at the Department of Precision Mechanical Engineering, Shanghai University. He received the B.S. degree and M.S. degree in Electrical and Electronic Engineering from Hunan University, China, in 1993 and 1995, the Ph.D. degree in Electronic and Information Engineering from Shanghai Jiaotong University, China, in 1998, and the Ph.D. degree in Mechanical Engineering from the University of Toronto, Canada, in 2008. Since 2010, he has been with Shanghai University and now serves as the Vice Dean of School of Mechatronic Engineering and Automation at Shanghai University. His research interests include optomechatronic systems; active vibration and noise control, adaptive control; Robotics. He has published 140+ refereed papers in the related areas.

Fanfan Qian is a lecturer at the Department of Mechanical Electronics, the University of Shanghai for Science and Technology. She received the B.S. degree and M.S. degree in the School of Engineering, Anhui Agricultural University, Anhui, China, in 2013 and 2016, the Ph.D. degree in the Department of Precision Mechanical Engineering, Shanghai University, Shanghai, China, in 2022. Her current research interests include active vibration control and active noise control.

Tianqi Liu received the B.S. degree from the Shandong Jianzhu University, Shandong, China, in 2020. She is currently working toward the M.S. degree with the Department of Precision Mechanical Engineering, Shanghai University, China. Her current research interests include adaptive active vibration control.

Azhar Iqbal holds a Ph.D. degree from the Department of Mechanical and Industrial Engineering, University of Toronto, in 2009 and Masters in Applied Sciences (MASc) from the University of Toronto Institute for Aerospace Studies (UTIAS) in 2005. His research work focuses on adaptive optics systems. Iqbal is currently working with the Ontario government as a Program Manager responsible for technology support to the Developmental Services program of the provincial government, and holds a Research Associate position with the Dunlap Institute of Astronomy at the University of Toronto.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, F., Ding, H., Wu, Z. et al. An improved stability compensation for feedforward active noise control systems with acoustic feedback. J Mech Sci Technol 38, 507–518 (2024). https://doi.org/10.1007/s12206-024-0101-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12206-024-0101-5

Keywords

Search

Navigation