Skip to main content

Active Suppression of Nonstationary Narrowband Acoustic Disturbances

  • Chapter
  • First Online:
Automatic Control, Robotics, and Information Processing

Abstract

In this chapter, a new approach to active narrowband noise control is presented. Narrowband acoustic noise may be generated, among others, by rotating parts of electro-mechanical devices, such as motors, turbines, compressors, or fans. Active noise control involves the generation of “antinoise”, i.e., the generation of a sound that has the same amplitude, but the opposite phase, as the unwanted noise, which causes them to interfere destructively, rather than constructively. In the range of low frequencies (below 1 kHz), the active approach is more effective than passive methods that employ dampers, barriers, absorbers, and other forms of acoustic isolation.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    Since in the case considered \(\omega (t)\) is a random variable (rather than an unknown deterministic constant) the classical Craméra-Rao bound does not apply.

References

  1. Nelson, P.A., Elliot, S.J.: Active Control of Sound. Academic Press, London (1993)

    Book  Google Scholar 

  2. Kuo, S.M., Morgan, D.: Active Noise Control Systems: Algorithms and DSP Implementations. Wiley, New York (1995)

    Google Scholar 

  3. van Trees. H.L., Bell K.L., Tian, Z.: Detection, Estimation and Modulation Theory, Part I: Detection, Estimation, and Filtering Theory. Wiley, New York (2013)

    Google Scholar 

  4. Morgan, D.R.: An analysis of multiple correlation cancellation loops with a filter in the auxiliary path. IEEE Trans. Acoust. Speech Signal Process. 28, 454–467 (1980)

    Article  Google Scholar 

  5. Crawford, D.H., Stewart, R.W.: Adaptive filtered-V algorithm for active noise control. J. Acoust. Soc. Am. 101, 2097–2103 (1997)

    Article  Google Scholar 

  6. Eriksson, L.J., Allie, M.C., Greiner, R.A.: The selection and application of an IIR adaptive filter for use in active sound attenuation. IEEE Trans. Acoust. Speech Signal Process. 35, 433–437 (1987)

    Article  Google Scholar 

  7. Eriksson, L.J.: Development of the filtered-U algorithm for active noise control. J. Acoust. Soc. Am. 89, 257–267 (1991)

    Article  Google Scholar 

  8. Skogestad, S., Postlethwaite, I.: Multivariate Feedback Control: Analysis and Design. Wiley, New York (2005)

    MATH  Google Scholar 

  9. Nehorai, A.: A minimal parameter adaptive notch filter with constrained poles and zeros. IEEE Trans. Acoust, Speech Signal Process. 33, 983–996 (1985)

    Google Scholar 

  10. Regalia, P.A.: An improved lattice-based adaptive IIR notch filter. IEEE Trans. Signal Process. 39, 2124–2128 (1991)

    Article  Google Scholar 

  11. Tichavský, P., Händel, P.: Two algorithms for adaptive retrieval of slowly time-varying multiple cisoids in noise. IEEE Trans. Signal Process. 43, 1116–1127 (1995)

    Article  MATH  Google Scholar 

  12. Schimidt, R.O.: Multiple Emiter Location and Signal Parameter Estimation. IEEE Trans. Antenn. Propag. 34, 276–280 (1986)

    Article  Google Scholar 

  13. Roy, R., Kailath, T.: ESPRIT - Estimation of Signal Parameters via Rotational Invariance Techniques. IEEE Trans. Acoust. Speech Signal Process. 37, 984–995 (1989)

    Article  MATH  Google Scholar 

  14. Bodson, M., Douglas, S.C.: Adaptive algorithms for the rejection of sinusoidal disturbances with unknown frequency. Automatica 33, 2213–2221 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  15. Bodson, M.: Rejection of periodic disturbances of unknown and time-varying frequency. Int. J. Adapt. Control Signal Process. 19, 67–88 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  16. Guo, X., Bodson, M.: Adaptive rejection of multiple sinusoids of unknown frequency. In: EUSIPCO 2007, Proceedings of the 2007 European Control Conference, pp. 121–128 (2007)

    Google Scholar 

  17. Åström, K.J., et al.: Theory and applications of self-tuning regulators. Automatica 13, 457–476 (1977)

    Article  MATH  Google Scholar 

  18. Landau, L.D., Constantinescu, A., Rey, D.: Adaptive narrow band disturbance rejection applied to an active suspension—an internal model principle approach. Automatica 41, 563–574 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  19. Silva, A.C., Landau, I.D., Airimitoaie, T.-B.: Direct adaptive rejection of unknown time-varying narrow band disturbances applied to a benchmark problem. Eur. J. Control 19, 326–336 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  20. Eriksson, L.J., Allie, M.C.: Use of random noise for on-line transducer modeling in an adaptive active attenuation system. J. Acoust. Soc. Am. 85, 797–802 (1989)

    Article  Google Scholar 

  21. Gan, W.S., Kuo, S.M.: An integrated active noise control headsets. IEEE Trans. Consum. Electron. 48, 242–247 (2002)

    Article  Google Scholar 

  22. Gan, W.S., Mitra, S., Kuo, S.M.: Adaptive feedback active noise control headset: implementation, evaluation and its extensions. IEEE Trans. Consum. Electron. 51, 975–982 (2005)

    Article  Google Scholar 

  23. Kuo, S.M., Chen, Y.-R., Chang, Ch-Y, Lai, Ch-W: Development and evaluation of light-weight active noise cancellation earphones. Appl. Sci. 8, 1178 (2018)

    Article  Google Scholar 

  24. Castae-Selga, R., Pea, R.: Active noise hybrid time-varying control for motorcycle helmets. IEEE Trans. Control Syst. Technol. 18, 602–612 (2010)

    Article  Google Scholar 

  25. Liu, L.C., Kuo, S.M., Raghuathan, K.: An audio integrated motorcycle helmet. J. Low Freq. Noise Vib. Active Control 29, 161–170 (2010)

    Google Scholar 

  26. Raghunathan, K., Kuo, S.M., Gan, W.S.: Active noise control for motorcycle helmets. In: Proceedings of the 2010 International Conference on Green Circuits and Systems, pp. 170–174. Shanghai, China (2010)

    Google Scholar 

  27. Wang, T.W., Gan, W.S., Kuo, S.M.: Subband-based active noise equalizer for motorcycle helmets. In: Proceedings of the 2010 ASIPA ASC 2010, pp. 555–559. Singapore (2010)

    Google Scholar 

  28. Chakrovorthy, S.R.: Active snore noise control systems. M.S. Thesis, Northern Illinois University (2005)

    Google Scholar 

  29. Chakravarthy, S., Kuo, S.M.: Application of active noise control for reducing snore. In: ICASSP 2006, Proceedings of the 2006 International Conference on Acoustics Speech and Signal Procesing, pp. 305–308. Toulose, France (2006)

    Google Scholar 

  30. Kuo, S.M., Gireddy, R.: Real-time experiment of snore active noise control. In: Proceedings of the 2007 International Conference on Control Applications, pp. 1085–1092. Singapore (2007)

    Google Scholar 

  31. Kuo, S.M., Liu, L., Gujjula, S.: Development and application of audio-integrated active noise control system for infant incubators. J. Noise Control Eng. 58, 163–175 (2010)

    Article  Google Scholar 

  32. Liu, L., Du, L., Kolla, A.: Wireless communication integrated hybrid active noise control system for infant incubators. In: Proceedings of the 2016 IEEE Signal Processing in Medicine and Biology Symposium, pp. 1–6. Philadelphia, USA (2016)

    Google Scholar 

  33. Yu, X., Gujjula, S., Kuo, S.M.:Active noise control for infant incubators. In: Proceedings of the 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 2531–2534. Minneapolis, USA (2009)

    Google Scholar 

  34. Chambers, J., Bullock, D., Kahana, Y., Kots, A., Palmer, A.: Developments in active noise control sound systems for magnetic resonance imaging. Appl. Acoust. 68, 281–295 (2007)

    Article  Google Scholar 

  35. Chen, C.K., Chiueh, T.T., Chen, J.H.: Active cancellation system of acoustic noise in MR imaging. IEEE Trans. Biomed. Eng. 46, 186–191 (1999)

    Article  Google Scholar 

  36. Kannan, G., Milani, A.A., Panahi, I., Briggs, R.W.: An efficient feedback active noise control algorithm based on reduced-order linear predictive modeling of fMRI acoustic noise. IEEE Trans. Biomed. Eng. 58, 3303–3309 (2011)

    Article  Google Scholar 

  37. Panahi, I.M.S.: Development of ANC methods for fMRI rooms: Design challenges and algorithms. In: Proceedings of the 2013 International Symposium on Image and Signal Processing and Analysis, pp. 655–660. Trieste, Italy (2013)

    Google Scholar 

  38. Takar, M.S., Kumar Sharma, M., Pal, R.: A review on evolution of acoustic noise reduction in MRI. In: Proceedings of the 2017 Recent Developments in Control, Automation Power Engineering, pp. 235–240. Noida, India (2017)

    Google Scholar 

  39. Kajikawa, Y., Gan, W.S., Kuo, S.M.: Recent advances on active noise control: open issues and innovative applications. APSIPA Trans Signal Inf. Process. 1, 1–21 (2012)

    Article  Google Scholar 

  40. Niedźwiecki, M., Meller, M.: A new a pproach to active noise and vibration control—Part I: the known frequency case. IEEE Trans. Signal Process. 57, 3373–3386 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  41. Söderström, T., Stoica, P.: System Identification. Prentice Hall, Englewood Cliffs, New Jersey (1988)

    MATH  Google Scholar 

  42. Van den Bos, A.: Complex gradient and Hessian. IEE Proc. Image Signal Process. 141, 380–382 (1994)

    Article  Google Scholar 

  43. Brandwood, D.H.: A complex gradient operator and its application in array theory. Proc. Inst. Elect. Eng. 130, 11–16 (1983)

    MathSciNet  Google Scholar 

  44. Haykin, S.: Adaptive Filter Theory. Prentice Hall, Englewood Cliffs (1996)

    MATH  Google Scholar 

  45. Wirtinger, W.: Zur formalen theorie der funktionen von mehr komplexen veränderlichen. Math. Ann. 97, 357–375 (1927)

    Article  MathSciNet  MATH  Google Scholar 

  46. Niedźwiecki, M.: Steady state and parameter tracking properties of self-tuning minimum variance regulators. Automatica 25, 597–602 (1989)

    Article  MATH  Google Scholar 

  47. Niedźwiecki, M., Meller, M.: A new a pproach to active noise and vibration control—Part II: the unknown frequency case. IEEE Trans. Signal Process. 57, 3387–3398 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  48. Bai, E.-W., Fu, L.-C., Sastry, S.: Averaging analysis for discrete time and sampled data adaptive systems. IEEE Trans. Circ. Syst. 35, 137–148 (1988)

    Article  MATH  Google Scholar 

  49. Niedźwiecki, M., Kaczmarek, P.: Tracking analysis of a generalized adaptive notch filter. IEEE Trans. Signal Process. 54, 304–314 (2006)

    Article  MATH  Google Scholar 

  50. Jury, M.: Theory and Application of the \({\cal{Z}}\)-transform Method. Wiley, New York (1964)

    Google Scholar 

  51. Niedźwiecki, M., Meller, M.: SONIC—Self-optimizing narrowband interference canceler: comparison of two frequency tracking strategies. In: Proceedings of the 8th IEEE International Conference on Control and Automation, pp. 1892–1896. Xiamen, China (2010)

    Google Scholar 

  52. Manolakis, D.G., Ingle, V.K., Kogon, S.M.: Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling, Adaptive Filtering, and Array Processing. McGraw-Hill, Boston (2000)

    Google Scholar 

  53. Niedźwiecki, M.: Identification of Time-Varying Processes. Wiley, New York (2000)

    Google Scholar 

  54. Niedźwiecki, M., Meller, M.: Hybrid SONIC: joint feedforward-feedback narrowband interference canceller. Int. Journ. Adaptive Contr. and Signal Process. 27, 1048–1064 (2013)

    Google Scholar 

  55. Niedźwiecki, M., Sobociński, A.: A simple way of increasing estimation accuracy of generalized adaptive notch filters. IEEE Signal Process. Lett. 14, 217–220 (2007)

    Article  Google Scholar 

  56. Niedźwiecki, M., Kaczmarek, P.: Generalized adaptive notch and comb filters for identification of quasi-periodically varying system. IEEE Trans. Signal Process. 53, 4599–4609 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  57. Niedźwiecki, M.: Adaptive notch smoothing revisited. In: EUSIPCO 2008, Proceedings of the 16th European Signal Processing Conference, pp. 1–5. Lausanne, Switzerland (2008)

    Google Scholar 

  58. Niedźwiecki, M.: Generalized adaptive notch smoothing revisited. IEEE Trans. Signal Process. 58, 1565–1576 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  59. Niedźwiecki, M., Meller, M.: New algorithms for adaptive notch smoothing. IEEE Trans. Signal Process. 59, 2024–2037 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  60. Niedźwiecki, M., Meller, M.: Self-optimizing adaptive vibration controller. IEEE Trans. Autom. Control 54, 2087–2099 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  61. Meller, M.: Samooptymalizujące adaptacyjne tłumienie zakłóceń wąskopasmowych. Ph.D. Dissertation, Politechnika Gdańska, Wydział Elektroniki, Telekomunikacji i Informatyki (2010)

    Google Scholar 

  62. Niedźwiecki, M., Meller, M.: An improved frequency estimator for an adaptive active noise control scheme. In: EUSIPCO 2010, Proceedings of the 18th European Signal Processing Conference, pp. 353–357. Aalborg, Denmark (2010)

    Google Scholar 

  63. Niedźwiecki, M., Meller, M.: Multifrequency self-optimizing narrowband interference canceller. In: IWAENC 2010, Proceedings of the 18th International Workshop on Acoustic Echo and Noise Control, pp. 1–4. Tel Aviv, Israel (2010)

    Google Scholar 

  64. Niedźwiecki M., Meller, M., Kajikawa, Y., Łukwiński, D.: Estimation of nonstationary harmonic signals and its application to active control of MRI noise. In: CASSP 2013, Proceedings of the 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 5661–5665. Vancouver, Canada (2013)

    Google Scholar 

  65. Niedźwiecki, M., Meller, M.: Generalized adaptive comb filters/smoothers and their application to the identification of quasi-periodically varying systems and signals. Automatica 49, 1601–1613 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  66. Meller M., Niedźwiecki, M.: Multiple-channel frequency-adaptive active vibration control using SONIC. In: ISPA 2013, Proceedings of the 8th International Symposium on Image and Signal Processing and Analysis, pp. 620–625. Trieste, Italy (2013)

    Google Scholar 

  67. Meller, M., Niedźwiecki, M.: Multichannel self-optimizing narrowband interference canceller. Signal Process. 98, 396–409 (2014)

    Article  Google Scholar 

  68. Niedźwiecki M., Meller, M.: Robust algorithm for active feedback control of narrowband noise. In: EUSIPCO 2015, Proceedings of the 23rd European Signal Processing Conference, pp. 275–279. Nice, France (2015)

    Google Scholar 

  69. Niedźwiecki M., Meller, M.: Active feedback noise control in the presence of impulsive disturbances. In: ICASSP 2015, Proceedings of the 2015 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 659–663. Brisbane, Australia (2015)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Maciej Niedźwiecki .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Niedźwiecki, M., Meller, M. (2021). Active Suppression of Nonstationary Narrowband Acoustic Disturbances. In: Kulczycki, P., Korbicz, J., Kacprzyk, J. (eds) Automatic Control, Robotics, and Information Processing. Studies in Systems, Decision and Control, vol 296. Springer, Cham. https://doi.org/10.1007/978-3-030-48587-0_26

Download citation

Publish with us

Policies and ethics