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Active Control of Tonal and Broadband Noise

  • Thomas KletschkowskiEmail author
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 56)

Abstract

Active reduction of disturbing noise requires the generation of appropriate control signals in order to drive the canceling sources. For this purpose we have to organize the signal processing of data provided by sensors. These data contain information about the disturbance as well as about the systems state. Because we assume that we are able to work with reference signals that are well correlated to the disturbing noise, the upcoming chapter is restricted to signal processing in feed-forward control systems. It starts with a mathematical preparation, because we will use some concepts of matrix calculus, see (Zurmühl in Matrizen und ihre technischen Anwendungen, Springer, Berlin, 1964) or (Strang in Introduction to linear algebra, Cambridge University Press, Wellesley, 1993). It is continued with an introduction to feed-forward control signal processing, before we discuss active control of both harmonic excitations and stochastic disturbances. Besides the topic of optimal control, attention is paid to adaptive control that enables the controller to track down non-stationary effects, e.g. the change of the operational speed of a turbo-machinery, or changes in the system response that can be caused by a change of environmental conditions such as ambient pressure, air temperature or humidity as well as by the warming-up of the electro-acoustic equipment. Adaptive feed-forward control of harmonic disturbances is discussed in frequency domain, whereas we will present four time domain approaches for adaptive feed-forward control of stochastic disturbances. However, this chapter is far away from presenting the basics of digital signal processing and digital filters as described in (Antoniou in Digital filters: analysis and design, McGraw-Hill, New York, 1979), (Bose in Digital filters—theory and applications, Elsevier, New York, 1985), (Diniz in Adaptive filtering—algorithms and practical implementations, Springer, New York, 2008), (Haykin in Adaptive filter theory, Prentice Hall, London, 1996), (Hess in Digitale Filter—Eine Einführung, Teubner, Stuttgart, 1989), (Johnson in Digitale Signalverarbeitung, Hanser, München in Cooperation with Prentice Hall International, London, 1991), and (Lücker in Grundlagen digitaler Filter—Eine Einführung in die Theorie linearer zeitdiskreter Systeme und Netzwerke, 1980) to review the theory of adaptive filtering as presented in (Farhang-Boroujeny in Adaptive filters—theory and applications, Wiley, New York, 1998), (Honig and Messerschmidt in Adaptive filters—structure, algorithms and applications, Kluwer Academic, Boston, 1984), (Sayed in Fundamentals of adaptive filtering, Wiley, Hoboken, 2003) and (Widrow and Stearns in Adaptive signal processing, Prentice Hall International, London, 1985) or to discuss DSP implementations, see (Akpan et al. in Active noise and vibration control literature survey: controller technologies. DREA-CR-1999-177, Contractor Report, Defence Research Establishment Atlantic, Dartmouth NS (CAN); MARTEC Ltd, Halifax NS (CAN); Sherbrooke Univ, Sherbrooke QUE (CAN), 1999) and (Chassaing in Digital signal processing and applications with the C6713 and C6416 DSK, Wiley, Canada, 2005). Its intension is to provide a basis for adaptive feed-forward control of low frequency interior noise that also includes algorithmic formulations of the control schemes. The content of the upcoming chapter is therefore oriented on (Kuo and Morgan in Active noise control systems—algorithms and DSP implementations, Wiley, Canada, 1996) and (Elliott in Signal processing for active noise control, Academic Press, London, 2001)—two fundamental books about signal processing for ANC that are (without detailed algorithmic formulations) summarized in (Kuo and Morgan in Proc. IEEE 87(6):943–973, 1999) and (Elliott in Tokhi and Veres (eds.) Active sound and vibration control, Institution of Electrical Engineers, London, pp. 57–72, 2002).

Keywords

Sound Pressure Source Strength Acoustic Resonance Acoustic Absorption Uncontrolled System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Department of Mechanical Engineering, MechatronicsHelmut-Schmidt-University/University of the Federal Armed Forces HamburgHamburgGermany

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