Adaptive Control, Filtering, and Signal Processing Aström, K.J.; Goodwin, G.C. and Kumar, P.R.

ISBN 10: 0387979883 / ISBN 13: 9780387979885

Editore: Springer, 1995

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Adaptive Control, Filtering, and Signal Processing | Aström, K.J.; Goodwin, C.C.; Kumar | Springer, 1995. In-8 cartonné, 396 pages. Couverture propre . Dos solide. Intérieur frais sans soulignage ou annotation. Exemplaire de bibliothèque : petit code barre en pied de 1re de couv., cotation au dos, rares et discrets petits tampons à l'intérieur de l'ouvrage. Très bon état général pour cet ouvrage. [BA67]. Codice articolo 0308UXJ5RMB

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Titolo: Adaptive Control, Filtering, and Signal ...

Casa editrice: Springer

Data di pubblicazione: 1995

Legatura: Hardcover

Condizione: Used: Very Good

Descrizione articolo

Riassunto:

The area of adaptive systems, which encompasses recursive identification, adaptive control, filtering, and signal processing, has been one of the most active areas of the past decade. Since adaptive controllers are fundamentally nonlinear controllers which are applied to nominally linear, possibly stochastic and time-varying systems, their theoretical analysis is usually very difficult. Nevertheless, over the past decade much fundamental progress has been made on some key questions concerning their stability, convergence, performance, and robustness. Moreover, adaptive controllers have been successfully employed in numerous practical applications, and have even entered the marketplace.

Contenuti:

Oscillations in systems with relay feedback.- Compatibility of stochastic and worst case system identification: Least squares, maximum likelihood and general cases.- Some results for the adaptive boundary control of stochastic linear distributed parameter systems.- LMS is H? optimal.- Adaptive control of nonlinear systems: A tutorial.- Design guidelines for adaptive control with application to systems with structural flexibility.- Estimation-based schemes for adaptive nonlinear state-feedback control.- An adaptive controller inspired by recent results on learning from experts.- Stochastic approximation with averaging and feedback: faster convergence.- Building models from frequency domain data.- Supervisory control.- Potential self-tuning analysis of stochastic adaptive control.- Stochastic adaptive control.- Optimality of the adaptive controllers.- Uncertain real parameters with bounded rate of variation.- Averaging methods for the analysis of adaptive algorithms.- A multilinear parametrization approach for identification of partially known systems.- Adaptive filtering with averaging.