Adaptive NN Control for a Flexible Manipulator With Input Backlash and Output Constraint
This article proposes an adaptive inverse neural network (NN) control of an uncertain flexible single-link manipulator with input backlash and output constraint. First, an adaptive inverse function is applied to eliminate the input backlash of the actuator. Second, an NN is applied to approximate the system uncertainty. Third, a barrier Lyapunov function is used to guarantee that the system is maintained within the constraints. Subsequently, the system’s semi-globally uniformly ultimately bounded stability is proved by the Lyapunov direct method. Finally, the simulation and experimental results manifest the feasibility of the proposed controller.
Authors
- Chenguang Yang (ORCID: https://orcid.org/0000-0001-5255-5559)
- Keum‐Shik Hong (ORCID: https://orcid.org/0000-0002-8528-4457)
- Zhijia Zhao (ORCID: https://orcid.org/0000-0002-5090-3801)
- Xing Li (ORCID: https://orcid.org/0000-0002-0794-3613)
- Xiaowei Wang (ORCID: https://orcid.org/0000-0003-2850-3585)
- Kaili Feng
Institutions
- Qingdao University (CN)
- Dongguan University of Technology (CN)
- Guangzhou University (CN)
- South China University of Technology (CN)
Publication Details
- Journal
- IEEE Transactions on Systems Man and Cybernetics Systems
- Published
- 2024-09-10
- DOI
- https://doi.org/10.1109/tsmc.2024.3450604
- Citations
- 10
- Primary Topic
- Adaptive Control of Nonlinear Systems
- Type
- article
- Field-Weighted Citation Impact
- 3.28
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Liaoning Province
- Basic and Applied Basic Research Foundation of Guangdong Province