Journal article
Adaptive neural network sliding mode control for Steer-by-Wire-based vehicle stability control
Journal of Intelligent & Fuzzy Systems, Vol.31(2), pp.885-902
2016
Abstract
This study develops a novel vehicle stability control (VSC) scheme using adaptive neural network sliding mode control technique for Steer-by-Wire (SbW) equipped vehicles. The VSC scheme is designed in two stages, i.e., the upper and lower level control stages. An adaptive sliding mode yaw rate controller is first proposed as the upper one to design the compensated steering angle for enabling the actual yaw rate to closely follow the desired one. Then, in the implementation of the yaw control system, the developed steering controller consists of a nominal control and a 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 actual front wheel steering angle can be driven to track the commanded angle in a finite time. The proposed novel stability control scheme possesses the following prominent superiorities over the existing ones: (i) No prior parameter information on the vehicle and tyre dynamics is required in stability control, which greatly reduces the complexity of the stability control structure. (ii) The robust stability control performance against parameter variations and road disturbances is obtained by means of ensuring the good tracking performance of yaw rate and steering angle and the strong robustness with respect to large and nonlinear system uncertainties. Simulation results are demonstrated to verify the superior control performance of the proposed VSC scheme.
Details
- Title
- Adaptive neural network sliding mode control for Steer-by-Wire-based vehicle stability control
- Authors/Creators
- H. Wang (Author/Creator) - Hefei University of TechnologyP. He (Author/Creator)M. Yu (Author/Creator) - Hefei University of TechnologyL. Liu (Author/Creator)M.T. Do (Author/Creator) - Swinburne University of TechnologyH. Kong (Author/Creator) - Hefei University of TechnologyZ. Man (Author/Creator) - Swinburne University of TechnologyZ. Xiao (Author/Creator)K. Li (Author/Creator)
- Publication Details
- Journal of Intelligent & Fuzzy Systems, Vol.31(2), pp.885-902
- Publisher
- IOS Press
- Identifiers
- 991005544897307891
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Journal article
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- Collaboration types
- Domestic collaboration
- International collaboration
- 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
- Computer Science