Adaptive approximately optimal control of unknown nonlinear systems based on locally weighted learning

This paper considers the optimal control of unknown nonlinear systems. Adaptive approximately optimal controllers are proposed with the aid of learning techniques. The proposed controllers can update themselves according to the estimates of the value functions and converge to the optimal controller. To show effectiveness of the proposed controllers, numerical simulations are presented.

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