Fault-Tolerant Control for Dynamic Positioning Vessel With Thruster Faults Based on the Neural Modified Extended State Observer

A new fault-tolerant control (FTC) method based on the neural modified extended state observer (NMESO) is proposed for dynamic positioning (DP) vessel with thruster faults in this article. Through incorporating a compound orthogonal neural network (CONN) into the design process of the modified exten...

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Veröffentlicht in:IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2021-09, Vol.51 (9), p.5905-5917
Hauptverfasser: Yu, Wenzhao, Xu, Haixiang, Han, Xin, Chen, Yahao, Zhu, Mengfei
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Sprache:eng
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Zusammenfassung:A new fault-tolerant control (FTC) method based on the neural modified extended state observer (NMESO) is proposed for dynamic positioning (DP) vessel with thruster faults in this article. Through incorporating a compound orthogonal neural network (CONN) into the design process of the modified extended state observer (MESO), the NMESO is developed to estimate the uncertainties in the DP control system, such as the environmental disturbances and the unknown dynamics, as well as the thruster faults simultaneously without knowing any prior information of them. With the help of the accurate estimation of the total uncertainties by NMESO, a PD-like feedback controller is established to realize the FTC of the DP vessel toward the thruster faults. By utilizing the Lyapunov stability analysis, it is proved that all the error signals in the closed-loop cascade system formed by the NMESO and PD-like feedback controller are uniformly ultimately bounded (UUB) and the bounds could be arbitrarily small by choosing appropriate parameters. Simulation experiments on two typical thruster fault scenarios are carried out to validate the effectiveness and the performance of the proposed NMESO-FTC compared with the conventional ESO-FTC. The simulation results show the proposed approach has better fault-tolerant performance.
ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2019.2956806