Distributed Collaborative Control of Multi-Vehicle Autonomous Cooperative Transportation Systems: A Hierarchical Constraint-Following Approach

• Published in: IEEE transactions on intelligent transportation systems Vol. 25; no. 5; pp. 4251 - 4264
• Main Authors: Zhang, Bowei, Huang, Jin, Su, Yanzhao, Chen, Ye-Hwa, Yang, Diange, Zhong, Zhihua
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Adaptive control; autonomous vehicles; Collaboration; Constraint modelling; constraint-following; Control theory; Cooperative control; Cooperative transportation systems; Dynamic models; Load modeling; Robust control; Task analysis; Topology; tracking control; Trajectory control; Transportation; Transportation systems; Uncertainty; Vehicle dynamics
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2023.3324759

In this paper, the dynamic modeling and collaborative control of a multi-vehicle cooperative transportation system for load carrying is explored. A hierarchical modeling and constraint-following control scheme is creatively proposed. In the dynamic modeling stage, the separate models of system components including the load and vehicle carriers are firstly established at the lower level. Then the internal and external constraints corresponding to the system topology and the transportation task are designed to integrate separate models at a higher level. In the system control stage, a distributed collaborative control law is proposed based on the closed-form constraint forces, with which the load can follow the external constraints actively and the carriers can maintain the internal constraints passively. In order to overcome the influence of time-varying multi-source uncertainties of the system on control effectiveness and stability, an adaptive robust control term is designed based on the Lyapunov min-max approach. Both uniform boundedness and uniform ultimate boundedness of the constraint-following error are guaranteed. Comprehensive validations show that our propose scheme can significantly reduce the modeling complexity despite the strongly coupled topology and nonlinearity of the system, as well as achieving more precise and robust trajectory following control compared with the baseline methods.