Distributed collaborative control of redundant robots under weight-unbalanced directed graphs

Zheng, Xin; Liu, Mei; Jin, Long; Yang, Chenguang

Abstract

In consideration of the limitation of the communication and the possibility that redundant robots might deliver information at different power levels, cases under weight-unbalanced directed graphs from the network topology perspective are in larger accordance with those in multiple redundant robot systems. By moving forward along this direction, a distributed controller is proposed in this paper to handle circumstances of collaborative control of multiple redundant robots under weight-unbalanced directed graphs. This kind of control problem is modelled into generalized quadratic programming (QP) problems with equality and inequality constraints. Then, the above QP problems are solved by a proposed neural-dynamics-based method, whose stability and convergence are theoretically proved subsequently. Besides, several experimental examples are conducted, and related comparisons are provided to demonstrate the feasibility of the proposed controller.

• Journal Article Type: Article
• Acceptance Date: Apr 4, 2023
• Online Publication Date: Apr 24, 2023
• Publication Date: Jan 31, 2024
• Deposit Date: May 9, 2023
• Publicly Available Date: May 10, 2023
• Journal: IEEE Transactions on Industrial Informatics
• Print ISSN: 1551-3203
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 20
• Issue: 1
• Pages: 681 - 690
• DOI: https://doi.org/10.1109/TII.2023.3268778
• Keywords: Distributed collaborative control, weight-unbalanced directed graph, neural dynamics, redundant robot, Robots, Robot kinematics, Directed graphs, Collaboration, Service robots, Informatics, Kinematics
• Public URL: https://uwe-repository.worktribe.com/output/10746677
• Publisher URL: https://ieeexplore.ieee.org/document/10107417