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Erschienen in:
2013 | OriginalPaper | Buchkapitel
NN Based Adaptive Dynamic Surface Control for Fully Actuated AUV
verfasst von : Baobin Miao, Tieshan Li, Weilin Luo, Xiaori Gao
Erschienen in: Advances in Neural Networks – ISNN 2013
Verlag: Springer Berlin Heidelberg
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In this brief, we consider the problem of tracking a desired trajectory for fully actuated autonomous underwater vehicle (AUV), in the presence of external disturbance and model errors. Based on the backstepping method and Lypunov stability theorem, we introduce the dynamic surface control (DSC) technique to tackle the problem of “explosion of complexity” which existing in the traditional backstepping algorithm. Furthermore, the norm of the ideal weighting vector in neural network (NN) systems is considered as the estimation parameter, such that only one parameter is adjusted. The proposed controller guarantees uniform ultimate bounded (UUB) of all the signals in the closed-loop system, while the tracking error converges to a small neighborhood of the origin. Finally, simulation studies are given to illustrate the effectiveness of the proposed algorithm.