In this chapter, a novel neuro-optimal tracking controlTracking control approach is developed towards discrete-time nonlinear systems. By constructing a new augmented plant, the optimal trajectory trackingTrajectory tracking design is transformed into an optimal regulationOptimal regulation problem. For discrete-time nonlinear dynamics, the steady controlSteady control input corresponding to the reference trajectoryReference trajectory is given. Then, the value-iteration-based tracking controlTracking control algorithm is provided and the convergence of the value functionValue function sequence is analyzed. Therein, the approximation errorApproximation error between the iterative value functionIterative value function and the optimal cost is estimated. The uniformly ultimately boundedUniformly ultimately bounded stability of the closed-loop system is also discussed in detail. Moreover, the iterative heuristic dynamic programming algorithm is implemented by involving the critic and action components, where some new updating rules of the action networkAction network are provided. Finally, two examples are used to demonstrate the optimality of the present controller as well as the effectiveness of the proposed method.


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    Title :

    Nonaffine Neuro-Optimal Tracking Control with Accuracy and Stability Guarantee


    Additional title:

    Intelligent Control & Learning Systems


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


    Publication date :

    2023-01-22


    Size :

    27 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English







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