The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Accurate Trajectory Tracking of Disturbed Surface Vehicles: A Finite-Time Control Approach
Abstract
In this paper, accurate trajectory tracking problem of a surface vehicle disturbed by complex marine environments is solved by creating a finite-time control (FTC) scheme whereby the nonsingular fast terminal sliding mode (NFTSM) and finite-time disturbance observer (FDO) techniques are deployed. Salient features are as follows. By devising an FDO, complex disturbances arising from marine environments can be exactly identified within a short time, in conjunction with the defined NFTSM manifold, and thereby contributing to exact trajectory tracking. Finite-time disturbance observation is completely decoupled from the nominal FTC scheme, and achieves stronger disturbance rejection and faster transient response, simultaneously. Both disturbance observation and trajectory tracking errors can exactly reach to zero in a finite time. Simulation results and comparisons are comprehensively conducted on CyberShip II and demonstrate remarkable superiority of the FTC scheme.
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Cites
From PID to Active Disturbance Rejection Control
Han, J. (2009) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2008.2011621 · Cited by 6,803
Continuous finite-time control for robotic manipulators with terminal sliding mode
Yu, S., Yu, X., Shirinzadeh, B., & Man, Z. (2005) · Automatica · doi:10.1016/j.automatica.2005.07.001 · Cited by 2,647
Non-singular terminal sliding mode control of rigid manipulators
Feng, Y., Yu, X., & Man, Z. (2002) · Automatica · doi:10.1016/s0005-1098(02)00147-4 · Cited by 2,322
A nonlinear disturbance observer for robotic manipulators
Chen, W.-H., Ballance, D. J., Gawthrop, P. J., & O'Reilly, J. (2000) · IEEE Transactions on Industrial Electronics · doi:10.1109/41.857974 · Cited by 1,752
Disturbance Observer Based Control for Nonlinear Systems
Chen, W.-H. (2004) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2004.839034 · Cited by 1,452
Fast terminal sliding-mode control design for nonlinear dynamical systems
Yu, X., & Zhihong, M. (2002) · IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications · doi:10.1109/81.983876 · Cited by 893
Smooth second-order sliding modes: Missile guidance application
Shtessel, Y. B., Shkolnikov, I. A., & Levant, A. (2007) · Automatica · doi:10.1016/j.automatica.2007.01.008 · Cited by 709
Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning
He, W., & Dong, Y. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2017.2665581 · Cited by 642
Jin, X. (2016) · Automatica · doi:10.1016/j.automatica.2016.01.064 · Cited by 510
Adaptive Robust Finite-Time Trajectory Tracking Control of Fully Actuated Marine Surface Vehicles
Wang, N., Qian, C., Sun, J.-C., & Liu, Y.-C. (2016) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2015.2496585 · Cited by 346
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Li, J., Ji, R., Liang, X., Ge, S. S., & Yan, H. (2022) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2022.3218574 · Cited by 659
An Overview of Finite/Fixed-Time Control and Its Application in Engineering Systems
Liu, Y., Li, H., Lu, R., Zuo, Z., & Li, X. (2022) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2022.105413 · Cited by 512
Self-citationReinforcement learning-based optimal tracking control of an unknown unmanned surface vehicle
Wang, N., Gao, Y., Zhao, H., & Ahn, C. K. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.3009214 · Cited by 322
Self-citationData-Driven Performance-Prescribed Reinforcement Learning Control of an Unmanned Surface Vehicle
Wang, N., Gao, Y., & Zhang, X. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3056444 · Cited by 282
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Metadata
- Authors
- Wang, N., Karimi, H. R., Li, H., & Su, S.-F.
- Venue
- IEEE/ASME Transactions on Mechatronics
- Published
- 2019-06
- Volume
- 24
- Issue
- 3
- Pages
- 1064-1074
- ISSN
- 1083-4435 (ISSN-L)
- 1941-014X
- OpenAlex
- W2923724424
- Cited by
- 258
- References
- 30
- FWCI
- 21.23
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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