Approximation-Error-ADP-Based Optimal Tracking Control for Chaotic Systems
In this chapter, an optimal tracking contrl scheme is proposed for a class of discrete-time chaotic systems using the approximation-error-based ADP algorithm. Via the system transformation, the optimal tracking problem is transformed into an optimal regulation problem, and then the novel optimal tracking control method is proposed. It is shown that for the iterative ADP algorithm with finite approximation error, the iterative performance index functions can converge to a finite neighborhood of the greatest lower bound of all performance index functions under some convergence conditions. Two examples are given to demonstrate the validity of the proposed optimal tracking control scheme for chaotic systems.
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