Trajectory tracking of redundantly actuated mobile robot by MPC velocity control under steering strategy constraint. (June 2022)

• Record Type: Journal Article
• Authors: Ding, Tao; Zhang, Yuhao; Ma, Guocai; Cao, Zhihong; Zhao, Xingwei; Tao, Bo
• Is Part Of: Mechatronics. Volume 84(2022)
• Publication Date: 2022-06
• Subjects: Four-wheel independent steering -- Redundantly-actuated omnidirectional mobile robot -- Model predictive control -- Steering fuzzy selector -- Pose correction -- Trajectory tracking control; Computer integrated manufacturing systems -- Periodicals; Flexible manufacturing systems -- Periodicals; Mechatronics -- Periodicals; Productique -- Périodiques; Fabrication, Systèmes flexibles de -- Périodiques; Mécatronique -- Périodiques; Computer integrated manufacturing systems; Flexible manufacturing systems; Mechatronics; Periodicals; 629.89
• DOI: 10.1016/j.mechatronics.2022.102779
• Languages: English
• ISSNs: 0957-4158

Abstract

Abstract: Four-wheel independent-steering redundantly-actuated omnidirectional mobile robot (FIR-OMR) has attracted wide attention for its excellent motion performance such as multi-mode steering and flexible attitude adjustment. However, for the 8-drive redundant and strong nonlinear system of FIR-OMR, the complexity and time-consuming of model solutions make it hard for the embedded system to achieve fast and efficient trajectory tracking. To copy with that, an optimal velocity model predictive control under steering strategy constraint (USSC-MPC) is presented, which is combined with pose correction by local micro error (LME-PC) for independent wheel angle feedback control. Specifically, the steering modes of FIR-OMR are divided into fixed independent wheel steering (IWS), zero-angle pure differential steering (DS), and Ackerman steering (AS), which is ultimately selected by steering fuzzy selector (SFS). Then a steer-based model prediction controller is designed to optimize the wheel velocity and the micro-error feedback wheel angle of pose correction pointing to the desired point is calculated by FIR-OMR in real-time. As a result, by controlling the wheel velocity and wheel angle, a satisfactory path tracking control effect can be obtained. In our proposed method, the USSC-MPC ensures the optimality of wheel velocity, and the LME-PC can achieve efficient trajectory tracking with a faster error convergence rate. Through simulations and experiments, complex motions such as multi-section paths and side parking can be realized, which verifies the feasibility and superiority of our method.