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LEARNING-BASED ADAPTIVE CONTROL


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Sinopse

Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained.Includes a good number of Mechatronics Examples of the techniques.Compares and blends Model-free and Model-based learning algorithms.Covers fundamental concepts, state-of-the-art research, necessary tools for modeling, and control.

Detalhes do Produto

    • Ano de Edição: 2016
    • Ano:  2016
    • País de Produção: United Kingdom
    • Código de Barras:  2001033780141
    • ISBN:  9780128031513

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