The idea of optimization can be regarded as an important basis of many disciplines and hence is extremely useful for a large number of research fields, particularly for artificial-intelligence-based advanced control design. Due to the difficulty of solving optimal controlOptimal control problems for general nonlinear systems, it is necessary to establish a kind of novel learning strategies with intelligent components. Besides, the rapid development of computer and networked techniques promotes the research on optimal controlOptimal control within the discrete-time domain. In this chapter, the bases, derivations, and recent progresses of critic intelligence for discrete-time advanced optimal controlAdvanced optimal control design are presented with an emphasis on the iterative framework. Among them, the so-called critic intelligenceCritic intelligence methodology is highlighted, which integrates learning approximators and the reinforcement formulation.


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    Titel :

    On the Critic IntelligenceCritic intelligence for Discrete-Time Advanced Optimal ControlAdvanced optimal control Design


    Weitere Titelangaben:

    Intelligent Control & Learning Systems


    Beteiligte:
    Wang, Ding (Autor:in) / Ha, Mingming (Autor:in) / Zhao, Mingming (Autor:in)


    Erscheinungsdatum :

    2023-01-22


    Format / Umfang :

    28 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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