Journal article
Neural-network-based robust control for steer-by-wire systems with uncertain dynamics
Neural Computing and Applications, Vol.26(7), pp.1575-1586
2015
Abstract
This study develops a neural-network-based robust control scheme for steer-by-wire systems with uncertain dynamics. The proposed control consists of a nominal control and a nonsingular terminal sliding mode compensator where a radial basis function neural network (RBFNN) is adopted to adaptively learn the uncertainty bound in the Lyapunov sense such that the effects of uncertainties can be effectively eliminated in the closed-loop system. Using the proposed neural control scheme, not only the robust steering performance against parameter variations and road disturbances is obtained, but also both the control gain and the control design complexity are greatly reduced due to the use of the RBFNN. Simulation results are demonstrated to verify the superior control performance of the proposed control scheme, in comparison with other control strategies.
Details
- Title
- Neural-network-based robust control for steer-by-wire systems with uncertain dynamics
- Authors/Creators
- H. Wang (Author/Creator) - Swinburne University of TechnologyZ. Xu (Author/Creator) - Lishui CA Steer-by-Wire Technological Co. Ltd., Zhejiang, ChinaM.T. Do (Author/Creator) - Swinburne University of TechnologyJ. Zheng (Author/Creator) - Swinburne University of TechnologyZ. Cao (Author/Creator) - Swinburne University of TechnologyL. Xie (Author/Creator) - Lishui University
- Publication Details
- Neural Computing and Applications, Vol.26(7), pp.1575-1586
- Publisher
- Springer
- Identifiers
- 991005544424807891
- Copyright
- © The Natural Computing Applications Forum 2015
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Journal article
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- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.29 Automation & Control Systems
- 4.29.1251 Vehicle Dynamics Control
- Web Of Science research areas
- Computer Science, Artificial Intelligence
- ESI research areas
- Engineering