Paperback : HK$1,300.00
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 late 1980s and early 1990s. 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, much fundamental progress has been 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. This book discusses this area.
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 late 1980s and early 1990s. 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, much fundamental progress has been 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. This book discusses this area.
Springer Book Archives
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.
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