Trajectory planning and tracking control of a ground mobile robot:A reconstruction approach towards space vehicle. (April 2019)

• Record Type: Journal Article
• Authors: Gu, Wanli; Cai, Shuo; Hu, Yunfeng; Zhang, Hui; Chen, Hong
• Is Part Of: ISA transactions. Volume 87(2019)
• Page Start: 116
• Page End: 128
• Publication Date: 2019-04
• Subjects: Nonlinear control -- Mobile robot -- Exponential stability -- Trajectory tracking control -- Trajectory planning -- Motion reconstruction; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2018.11.019
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: With the development of the similarity calculation method, the orbital motion of space vehicle can be translated into a sequence of waypoints that reflect position and velocity on the ground. In this paper, a motion control system is proposed to make the mobile robot pass through the desired waypoints for reconstructing the orbital motion. First, the parameterized trajectory optimization method is applied to generate a curvature-continuous trajectory from the waypoints, the position and velocity demands are presented as the equality constraints. Virtual positions are introduced to reduce the oscillation, and the total execution time of the whole trajectory is selected as the optimization parameter to reduce the computational burden. Then, an equivalence transformation is provided to translate the error system into an affine form, which is beneficial for the feedback controller design. Based on this, a nonlinear trajectory tracking controller is proposed, which includes a feedforward controller and an error feedback controller, and its exponential stability is proved using Persistency of Excitation Lemma. In addition, a shunting neural dynamics model is employed to avoid sharp velocity jumps. Finally, the performed experiments verify the effectiveness of the proposed method. Highlights: The virtual position and non-uniform approximation method are used to model curvature-continuous trajectory. An affine error system is deduced based on an equivalence transformation. The exponential stability of the closed-loop system is proved. The shunting neural dynamics model is employed to avoid sharp velocity jumps.