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Adaptive neural network control of underactuated surface vessels with guaranteed transient performance: Theory and experimental results

Chen, Lepeng; Cui, Rongxin; Yang, Chenguang; Yan, Weisheng

Authors

Lepeng Chen

Rongxin Cui

Weisheng Yan



Abstract

In this paper, an adaptive trajectory tracking
control algorithm for underactuated unmanned surface
vessels (USVs) with guaranteed transient performance is
proposed. To meet the realistic dynamical model of USVs,
we consider that the mass and damping matrices are not
diagonal and the input saturation problem. Neural Networks
(NNs) are employed to approximate the unknown external
disturbances and uncertain hydrodynamics of USVs. Moreover,
both full state feedback control and output feedback
control are presented, and the unmeasurable velocities of
the output feedback controller are estimated via a highgain
observer. Unlike the conventional control methods,
we employ the error transformation function to guarantee
the transient tracking performance. Both simulation and
experimental results are carried out to validate the superior
performance via comparing with traditional potential integral
(PI) control approaches.

Journal Article Type Article
Journal IEEE Transactions on Industrial Electronics
Print ISSN 0278-0046
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Pages 1-1
Institution Citation Chen, L., Cui, R., Yang, C., & Yan, W. (in press). Adaptive neural network control of underactuated surface vessels with guaranteed transient performance: Theory and experimental results. IEEE Transactions on Industrial Electronics, 1-1. https://doi.org/10.1109/TIE.2019.2914631
DOI https://doi.org/10.1109/TIE.2019.2914631
Keywords neural network, underactuated surface vessel, guaranteed transient performance
Publisher URL http://doi.org/10.1109/TIE.2019.2914631
Additional Information Additional Information : (c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

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