Adaptive sliding mode control for 4–wheel SBW system with Ackerman geometry. (January 2020)

• Record Type: Journal Article
• Authors: Liu, Changrui; Sun, Weichao; Zhang, Jinhua
• Is Part Of: ISA transactions. Volume 96(2020)
• Page Start: 103
• Page End: 115
• Publication Date: 2020-01
• Subjects: Adaptive control -- Sliding mode control -- Steer-by-Wire -- Ackerman geometry -- 4 wheel vehicles; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2019.06.027
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: In this paper, the modeling of front wheels Steer-by-Wire (SBW) system is further developed into 4-wheel SBW (4WSBW) system for electric vehicles with Ackerman Geometry taken into consideration. Moreover, a novel adaptive integral terminal sliding mode control (AITSMC) scheme is presented to control the wheel steering angles in both single-wheel situation and four-wheel situation. Based on Lyapunov criterion, stability proof guarantees that the tracking error in closed-loop converges to zero in finite time. In comparison with Proportional–Integral–Derivative (PID) based control, terminal sliding mode control (TSMC) and adaptive TSMC (ATSMC), the proposed control scheme only requiring information of the inertia of the wheels and the motors possesses two major advantages. First, robustness and finite-time convergence are ensured without obtaining information of disturbances caused by road conditions and parameters of viscous friction. Second, tracking error is further suppressed with noise impact in feedback loop caused by sensors while maintaining fast convergence rate. The synthesized performance of the 4WSBW vehicles is significantly improved and numerical simulations are conducted on the dynamic model of the system to corroborate the merits of the proposed control scheme. Highlights: Original controller is first designed for 4 Wheel Steer-by-Wire System. Ackerman Geometry and coupling between wheels are firstly considered. Tracking error in transient dynamic is further suppressed. Optimized adaptive laws for road detection is successfully implemented. High frequency fluctuation in control input caused by noise is resolved.