Coupled fractional-order sliding mode control and obstacle avoidance of a four-wheeled steerable mobile robot. (February 2021)

• Record Type: Journal Article
• Authors: Xie, Yuanlong; Zhang, Xiaolong; Meng, Wei; Zheng, Shiqi; Jiang, Liquan; Meng, Jie; Wang, Shuting
• Is Part Of: ISA transactions. Volume 108(2021)
• Page Start: 282
• Page End: 294
• Publication Date: 2021-02
• Subjects: Coupled fractional-order sliding mode control -- Four-wheeled steerable mobile robot -- Near-time-optimal potential function -- Obstacle avoidance; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2020.08.025
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: Recently, four-wheeled steerable mobile robots (FSMR) have attracted increasing attention in industrial fields, however the collision-free trajectory tracking control is still challenging in dynamic environments. This paper studies a new coupled fractional-order sliding mode control (CFSMC) and obstacle avoidance scheme, which has superior capacities of providing more control flexibilities and achieving high-accuracy. Instead of exploring traditional integer-order solutions, novel fractional-order sliding surfaces are proposed to handle the nonlinear interconnected states in a coupled structure. To accomplish non-oscillating avoidance of both stationary and moving entities within an uncertain workspace, a modified near-time-optimal potential function is subsequently presented with improved efficiency and reduced collision-resolving distances. By utilizing fuzzy rules, proper adaption gains of the reaching laws are designed to degenerate the effect of undesired chattering. The asymptotic stability and convergence can be guaranteed for the resultant closed-loop system. Three experiments are implemented on a real-time FSMR system. The results validate the reliability of the presented CFSMC scheme in terms of significantly mitigated following errors, faster disturbance rejection and smooth transition as compared to conventional methods. Highlights: A novel CFSMC with FO sliding surface vector is designed. A near-time-optimal potential function is presented for obstacle avoidance. The slope coefficients of the reaching laws are regulated adaptively. The proposed method is verified by comparative experiments.