- Title
- An adaptive hierarchical sliding mode controller for autonomous underwater vehicles
- Creator
- Van Vu, Quang; Dinh, Tuan; Van Nguyen, Thien; Tran, Hoang; Nguyen, Linh
- Date
- 2021
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/179990
- Identifier
- vital:15714
- Identifier
-
https://doi.org/10.3390/electronics10182316
- Identifier
- ISBN:2079-9292 (ISSN)
- Abstract
- The paper addresses a problem of efficiently controlling an autonomous underwater vehicle (AUV), where its typical underactuated model is considered. Due to critical uncertainties and nonlinearities in the system caused by unavoidable external disturbances such as ocean currents when it operates, it is paramount to robustly maintain motions of the vehicle over time as expected. Therefore, it is proposed to employ the hierarchical sliding mode control technique to design the closed-loop control scheme for the device. However, exactly determining parameters of the AUV control system is impractical since its nonlinearities and external disturbances can vary those parameters over time. Thus, it is proposed to exploit neural networks to develop an adaptive learning mechanism that allows the system to learn its parameters adaptively. More importantly, stability of the AUV system controlled by the proposed approach is theoretically proved to be guaranteed by the use of the Lyapunov theory. Effectiveness of the proposed control scheme was verified by the experiments implemented in a synthetic environment, where the obtained results are highly promising. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Linh Nguyen" is provided in this record**
- Publisher
- MDPI
- Relation
- Electronics (Switzerland) Vol. 10, no. 18 (2021), p.
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- https://creativecommons.org/licenses/by/4.0/
- Rights
- Copyright © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
- Rights
- Open Access
- Subject
- 0906 Electrical and Electronic Engineering; Adaptive learning; Autonomous underwater vehicle; Hierarchical sliding mode control; Lyapunov theory; Neural network; Under-actuated system
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