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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    Title :

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


    Additional title:

    Intelligent Control & Learning Systems


    Contributors:
    Wang, Ding (author) / Ha, Mingming (author) / Zhao, Mingming (author)


    Publication date :

    2023-01-22


    Size :

    28 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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