Approximate optimal control for an uncertain robot based on adaptive dynamic programming

Abstract An approximate optimal scheme is proposed for an uncertain n-link robot subject to saturation non-linearity. A remarkable feature is that compared with the previous results, the model uncertainty in robotic dynamic is taken into account in the paper. Under the frame of adaptive dynamic programming (ADP), an optimal control is designed for the nominal robotic system and proved to be an approximate optimal control of the unknown robotic system, and it not only stabilizes the unknown system, but also decreases the control cost. Furthermore, the saturation non-linearity is also solved with generalized non-quadratic functional. According to the Lyapunov theory, all the error signals can be proved to be uniformly ultimately bounded (UUB). Simulation examples are implemented to validate the effectiveness of the designed method.

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