Intelligent methods for active noise and vibration control

• Autorzy: Tokhi M. O.
• Języki publikacji: EN

Abstrakty

EN

This paper presents an overview of intelligent soft computing techniques within the framework of active control of noise and vibration. Tools considered include genetic algorithms (GAs), neural networks (NNs) and fuzzy logic (FL). The paper highlights associated merits and potential benefits of the approaches in modelling and control of dynamic systems. These are demonstrated in the control of noise in free-field propagation and vibration suppression in 1D and 2D flexible structures. The paper shows that the potential benefits of the individual components can be exploited and approaches for design and development of hybrid soft-computing algorithms devised for modelling and control of dynamic systems. It is demonstrated that significant benefits in terms of performance can be gained with such hybrid algorithms.

Słowa kluczowe

EN

active noise control; active vibration control; fuzzy logic; genetic algorithms; neural network; modelling of dynamic systems

• Wydawca: Instytut Podstawowych Problemów Techniki PAN ; Komitet Akustyki PAN ; Polskie Towarzystwo Akustyczne
• Czasopismo: Archives of Acoustics
• Rocznik: 2004
• Tom: Vol. 29, no. 2
• Strony: 259--273
• Opis fizyczny: Bibliogr. 13 poz., rys., wykr.

Twórcy

autor

Tokhi M. O.

• The University of Sheffield, Department of Automatic Control and Systems Engineering, Sheffield, United Kingdom,

Bibliografia

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• [11] SHARMA S. K., TOKHI M. O., Neural network optimisation using genetic algorithm: A hierarchical fuzzy method, Proceedings of AARTC00: IFAC Workshop on Algorithms and Architectures for Realtime Control, Palma de Mallorca (Spain), 15-17 May 2000, pp. 71–76.
• [12] SIDDIQUE M. N. H., TOKHI M. O., GA-based neuro-fuzzy controller for flexible-link manipulator, Proceedings of IEEE International Conference on Control Applications, Glasgow, 18–20 September 2002, pp. 471–476.
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