Adaptive Control: Stability, Convergence, and Robustness
Shankar Sastry | 1989-01-01 00:00:00 | Prentice Hall | 378 | Control Theory
The objective of this book is to give, in a concise and unified fashion, the major results, techniques of analysis and new directions of research in adaptive systems. Such a treatment is particularly timely, given the rapid advances in microprocessor and multi-processor technology which make it possible to implement the fairly complicated nonlinear and time varying control laws associated with adaptive control. Indeed, limitations to future growth can hardly be expected to be computational, but rather from a lack of a fundamental understanding of the methodologies for the design, evaluation and testing of the algorithms. The objective has been to give a clear, conceptual presentation of adaptive methods, to enable a critical evaluation of these techniques and suggest avenues of further development.
Adaptive control has been the subject of active research for over three decades now (ed note: this book was published in 1994). There have been many theoretical successes, including the development of rigorous proofs of stability and an understanding of the dynamical properties of adaptive schemes. Several successful applications have been reported and the last ten years have seen an impressive growth in the availability of commercial adaptive controllers.
This book presents the deterministic theory of identification and adaptive control. For the most part the focus is on linear, continuous time, single-input single-output systems. The presentation includes the algorithms, their dynamical properties and tools for analysis - including the recently introduced averaging techniques. Current research in the adaptive control of multi-input, multi-output linear systems and a class of nonlinear systems is also covered. Although continuous time algorithms occupy the bulk of our interest, they are presented in such a way as to enable their transcription to the discrete time case.
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