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Böcker av Weihai Zhang

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  • av Yaning Lin
    1 137

    The book focuses on Pareto optimality in cooperative games. Most of the existing works focus on the Pareto optimality of deterministic continuous-time systems or for the regular convex LQ case. To expand on the available literature, we explore the existence conditions of Pareto solutions in stochastic differential game for more general cases. In addition, the LQ Pareto game for stochastic singular systems, Pareto-based guaranteed cost control for uncertain mean-field stochastic systems, and the existence conditions of Pareto solutions in cooperative difference game are also studied in detail.Addressing Pareto optimality for more general cases and wider systems is one of the major features of the book, making it particularly suitable for readers who are interested in multi-objective optimal control. Accordingly, it offers a valuable asset for researchers, engineers, and graduate students in the fields of control theory and control engineering, economics, management science, mathematics, etc.

  • av Weihai Zhang
    671

    The H control has been one of the important robust control approaches since the 1980s. This book extends the area to nonlinear stochastic H2/H control, and studies more complex and practically useful mixed H2/H controller synthesis rather than the pure H control. Different from the commonly used convex optimization method, this book applies

  • av Weihai Zhang
    2 661

    The H¿ control has been one of the important robust control approaches since the 1980s. This book extends the area to nonlinear stochastic H2/H¿ control, and studies more complex and practically useful mixed H2/H¿ controller synthesis rather than the pure H¿ control. Different from the commonly used convex optimization method, this book applies the Nash game approach to give necessary and sufficient conditions for the existence and uniqueness of the mixed H2/H¿ control. Researchers will benefit from our detailed exposition of the stochastic mixed H2/H¿ control theory, while practitioners can apply our efficient algorithms to address their practical problems.

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