Journal
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume 67, Issue 5, Pages 4024-4035Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2019.2914631
Keywords
Transient analysis; Adaptation models; Damping; Artificial neural networks; Output feedback; Uncertainty; Sea surface; Adaptive output feedback control; guaranteed transient performance; input saturation; underactuated surface vessel
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Funding
- National Natural Science Foundation of China (NSFC) [U1813225, 61633002, 61472325]
- Science, Technology and Innovation Commission of Shenzhen Municipality [JCYJ20170817145216803]
- Doctorate Foundation of Northwestern Polytechnical University [CX201904]
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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 high-gain 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 control approaches.
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