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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| Vydáno v: | Control engineering practice Ročník 136; s. 105535 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier Ltd
01.07.2023
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| Témata: | |
| ISSN: | 0967-0661, 1873-6939 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | 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. |
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| ISSN: | 0967-0661 1873-6939 |
| DOI: | 10.1016/j.conengprac.2023.105535 |