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Article type: Research Article
Authors: Sun, Zhea; * | Zheng, Jinchuanb | Man, Zhihongb | Wang, Haic | Shao, Ked | He, Defenga
Affiliations: [a] College of Information Engineering, Zhejiang University of Technology, Hangzhou, China | [b] Faculty of Science, Engineering & Technology, Swinburne University of Technology, Melbourne, Australia | [c] College of Science, Health, Engineering and Education, Murdoch University, Perth, Australia | [d] School of Mechanical Engineering, Hefei University of Technology, Hefei, China
Correspondence: [*] Corresponding author. Zhe Sun, College of Information Engineering, Zhejiang University of Technology, Hangzhou, China. E-mail: [email protected].
Abstract: This paper presents a novel adaptive fuzzy sliding mode (AFSM) control scheme for a vehicle steer-by-wire (SbW) system. Initially, the dynamics of the SbW system are described by a second-order differential equation where the Coulomb friction and the self-aligning torque are treated as external disturbances. Furthermore, an AFSM controller is designed for the SbW system, which utilizes an adaptive law to estimate both the Coulomb friction and the self-aligning torque, a sliding mode control component to deal with the parametric uncertainties and unmodeled dynamics, and a fuzzy strategy to strike a good balance between the chattering-alleviation and the tracking precision. The stability of the control system is verified in the sense of Lyapunov, and the selection of control parameters is provided in detail. Lastly, experiments are carried out under various road conditions. The experimental results demonstrate that the developed AFSM controller possesses superiority in terms of higher tracking accuracy, stronger robustness and a better balance between the control precision and smoothness in comparison with a conventional sliding mode (CSM) controller and a boundary layer-based adaptive sliding mode (BLASM) controller.
Keywords: Adaptive fuzzy sliding mode (AFSM), steer-by-wire (SbW), vehicle, self-aligning torque
DOI: 10.3233/JIFS-182824
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6601-6612, 2019
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