A Novel Feasibility Condition-Free Approach for Achieving Desired Precision and Unified Performance Within Prescribed Time
This paper proposes a low-complexity tracking control framework for uncertain nonlinear systems in strict feedback and normal forms, respectively. By leveraging a smooth scaling function, these control schemes ensure unified prescribed performance for the output tracking error of strict feedback nonlinear systems and the full-state tracking errors of normal form nonlinear systems. The notion of unified prescribed performance allows for different performance behaviors via performance functions, which can be either constant or time-varying with arbitrarily large initial values. The main contribution is achieving unified prescribed performance for full-state tracking errors without imposing feasibility conditions, a limitation of existing approaches. To eliminate these strict conditions, we introduce a uniform transformation independent of initial conditions. Additionally, the proposed control schemes are low-complexity since they do not require adaptive mechanisms or function approximation to deal with uncertainties and disturbances. The effectiveness of these frameworks is demonstrated through comparative analysis.
Authors
- Xiang Xu (ORCID: https://orcid.org/0000-0002-8663-9029)
- He Kong (ORCID: https://orcid.org/0000-0002-1382-4186)
- Yongduan Song (ORCID: https://orcid.org/0000-0002-2167-1861)
- Guang‐Ren Duan (ORCID: https://orcid.org/0000-0002-8169-2218)
- Mehdi Golestani (ORCID: https://orcid.org/0000-0001-5331-2524)
- Tao Liu (ORCID: https://orcid.org/0000-0001-8068-8025)
Institutions
- Chongqing University (CN)
- Southern University of Science and Technology (CN)
Publication Details
- Journal
- IEEE Transactions on Circuits and Systems I Regular Papers
- Published
- 2025-04-15
- DOI
- https://doi.org/10.1109/tcsi.2025.3552602
- Citations
- 1
- Primary Topic
- Advanced Measurement and Metrology Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.71
Funders
- National Natural Science Foundation of China