In this study, the problem of adaptive dynamic surface control (DSC) design is investigated for a class of stochastic non-linear systems with input saturation. The saturation non-linearity is modelled via the existing...
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In this study, the problem of adaptive dynamic surface control (DSC) design is investigated for a class of stochastic non-linear systems with input saturation. The saturation non-linearity is modelled via the existing dead zone-based model of saturation. Furthermore, the packaged unknown functions are tackled using the neural networks. On the basis of the DSC technique, an adaptive controller is designed for stochastic non-linear systems with input saturation. The proposed control scheme can guarantee the closed-loop system stability, which shows that all closed-loop system signals are semi-globally uniformly ultimately bounded in the sense of probability and the tracking error converges to a small neighbourhood of the origin. Simulation results are provided to demonstrate the effectiveness and performance of the proposed approach.
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