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• W2126970165 abstract "Control of acoustic systems is a challenging problem for several reasons. Some primary reasons include computational complexity resulting from very high-order models, nonminimum phase behavior introduced by finite dimensional approximations and transportation delays, uncertainties introduced by non-uniform boundary conditions, and acoustic interaction with the dynamics of the enclosure structure. Until recently, most active noise control techniques focused on feedforward cancellation. It is only in the last few years that attempts have been made to use feedback for active noise control. Work by Hu and co-workers is remarkable for its thoroughness in setting up the system model, the theoretical analysis, and providing experimental demonstrations. 1-3 The work by Bernstein and co-workers also provides a solid analysis and application of feedback control. 4 Other examples of feedback control approaches are direct-rate feedback 5 and pole placement. 6 Much work continues towards the design and analysis of feedback control methods for achieving broadband reduction which is also robust to uncertainties. Acoustic ducts have certain dynamic characteristics that make it difficult to design an active feedback controller. Firstly, the model has no natural roll-off at high frequencies and it is modally very rich. Also, the frequency response is characterized by resonant peaks which dominate the dynamics. In the presence of these characteristics, any uncertainty in the system model has a significant affect on closed-loop stability. Much of the design of feedback controllers for acoustic systems is based on models identified using experimental frequency response. Acoustic ducts in the form of heating, ventilation, air-conditioning, and exhaust ducts form a significant category of systems which need active noise control. An ability to derive analytical models for this class of systems will be most helpful in developing controllers for active noise control. A simple method using symbolic computation is presented in Ref. 7 to derive models for virtually any configuration of an acoustic duct. The analytically derived model for an acoustic duct is linear, time-invariant, and infinite-dimensional. For most control designs, however, a finite-dimensional approximation is needed. In this paper, a finite-dimensional approximation model is obtained using an assumed modes approach. A detailed discussion of the modelling and identification of acoustic ducts can be found in Ref. 7. The control design methodology used in this paper is based on passivity theory. An experimental validation of the passivity-based robust control design methodology based on the ideas given in Refs. 8-12 is presented. It is shown that controllers designed using passivity theory can achieve broadband reduction of noise. It is also shown that the controller design is not only robust to unmodelled dynamics (higher order modes) and modelling errors, but also to parametric variations. The experimental verification demonstrates the efficacy of the controller. To facilitate understanding of passivity-based control design as presented in later sections of this paper a brief review of passivity-based control is given next." @default.
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• W2126970165 date "2003-01-01" @default.
• W2126970165 modified "2023-09-25" @default.
• W2126970165 title "Robust broadband control of acoustic noise in ducts: a passivity-based approach" @default.
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• W2126970165 doi "https://doi.org/10.3397/1.2839703" @default.
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