Robust trajectory tracking and control allocation of X-rudder AUV with actuator uncertainty

This paper proposes a robust trajectory tracking control method for an X-rudder autonomous underwater vehicle subject to imprecise model parameters, unknown disturbances, and actuator uncertainty. The control scheme consists of a kinematics controller, dynamics controller, and rudder allocator const...

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Bibliographic Details
Published in:Control engineering practice Vol. 136; p. 105535
Main Authors: Wang, Wenjin, Wen, Tao, He, Xiao, Xu, Guohua
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.07.2023
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ISSN:0967-0661, 1873-6939
Online Access:Get full text
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Summary:This paper proposes a robust trajectory tracking control method for an X-rudder autonomous underwater vehicle subject to imprecise model parameters, unknown disturbances, and actuator uncertainty. The control scheme consists of a kinematics controller, dynamics controller, and rudder allocator constructed using backstepping techniques. The kinematics controller employs a line-of-sight guidance law, while the dynamics controller uses integral sliding mode and a Radial Basis Function Neural Network to handle modeling errors and unknown disturbances. Finally, a Recursive Least Square Control Allocation method is developed to minimize the allocation error considering the uncertainty in the control effectiveness matrix by solving a dual second-order cone programming problem. Simulation results demonstrate that the RBFNN-based trajectory tracking method achieves satisfactory performance in the presence of time-varying environmental disturbances, and the Recursive Least Square Control Allocation method effectively deals with actuator uncertainty. •A RBFNN-based trajectory tracking controller is proposed to better approximate the dynamics uncertainties and disturbances.•A method of Recursive Least Squares Control Allocation is proposed to minimize the errors in the X-rudder AUV control.•The cascaded tracking controller is practical and feasible for AUVs as it does not depend on accurate model information.
ISSN:0967-0661
1873-6939
DOI:10.1016/j.conengprac.2023.105535