标题:Finite-time Controller Design for Four-wheel-steering of Electric Vehicle Driven by Four In-wheel Motors
作者:Meng, Qinghua; Sun, Zong-Yao; Li, Yushan
作者机构:[Meng, Qinghua] Hangzhou Dianzi Univ, Sch Mech Engn, Hangzhou 310018, Zhejiang, Peoples R China.; [Sun, Zong-Yao] Qufu Normal Univ, Inst Automat, Qu 更多
通讯作者:Meng, Qinghua
通讯作者地址:[Meng, QH]Hangzhou Dianzi Univ, Sch Mech Engn, Hangzhou 310018, Zhejiang, Peoples R China.
来源:INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
出版年:2018
卷:16
期:4
页码:1814-1823
DOI:10.1007/s12555-017-0509-0
关键词:Electric vehicle; finite-time convergence; four-wheel-steering;; stability control
摘要:A smooth control method may do not obtain a desired convergence. On the other hand, a no-continuous method may cause a close-loop system to chatter. In order to avoid the aforementioned disadvantages, a non-smooth finite-time control method is proposed and applied on an active four-wheel-steering electric vehicle driven by four in-wheel motors to improve the safety and manoeuvrability in this paper. Based on an ideal electric vehicle steering tracking model, a non-smooth finite-time convergence controller is constructed for controlling the four wheels' steering angles of an electric vehicle. The front wheel cornering stiffness, rear wheel cornering stiffness and external disturbance of a practical car are regarded as bounded uncertain parameters according to practical conditions. An A-class car model in the Carsim software is utilized to simulate the designed controller. The simulation results show that the controller based on finite-time convergence can track the ideal vehicle steering model better to obtain zero sideslip angle and expected yaw rate even when there exist perturbation of cornering stiffness and disturbance of lateral wind. It means the control system of the electric vehicle is robust with uncertainty. The simulation results also show that the non-smooth finite-time control method is better than the slide mode control method for the active four-wheel-steering system of the electric vehicle.
收录类别:EI;SCIE
资源类型:期刊论文
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