Practical Prescribed-Time Control for Constrained Human–Robot Co-Transportation With Velocity Observer and Obstacle Avoidance
It is greatly desirable to carry out the secure practical prescribed-time human-robot co-transportation task. The implementation of such application becomes even more theoretical and practical challenge if uncertainties in the robot model, unmeasured velocity vector and multiple-dynamic-obstacles environment are involved, yet certain behavior indices are also pursued. In this work, a settling time regulator is introduced and it is integrated with the dynamic surface-based backstepping design embedded with specific system transformation. This results in a solution that both constrained and unconstrained cases can be accommodated uniformly, concurrently, the settling time and tracking precision can be preset by user as required. Furthermore, a fuzzy velocity observer is designed with aid of the fuzzy logic technique, which is nontrivial to perform a control design of robot dynamics with unmeasured velocity vector and modeling uncertainties. In particular, benefiting from integral multiplicative barrier-Lyapunov function, an improved adaptive obstacle-avoiding controller is designed, which, without control singular issue, is capable of achieving desired tracking while avoiding obstacles encountered. The validity and benefits of the resultant control strategy are eventually substantiated via the simulation results of a two-DOF robotic manipulator.
Authors
- Yulian Jiang (ORCID: https://orcid.org/0000-0001-9304-3269)
- Yanzheng Zhu (ORCID: https://orcid.org/0000-0001-5160-9623)
- Shenquan Wang (ORCID: https://orcid.org/0000-0002-8284-2396)
- Wen Yang (ORCID: https://orcid.org/0009-0005-6844-7452)
- Hongjing Liang (ORCID: https://orcid.org/0000-0003-1480-1872)
Institutions
- University of Electronic Science and Technology of China (CN)
- Changchun University of Technology (CN)
- Shandong University of Science and Technology (CN)
Publication Details
- Journal
- IEEE Transactions on Systems Man and Cybernetics Systems
- Published
- 2024-11-13
- DOI
- https://doi.org/10.1109/tsmc.2024.3489587
- Citations
- 7
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 4.50
Funders
- National Natural Science Foundation of China