Abstract
This paper investigates the practical prescribed-time control problem for uncertain high-order strict-feedback systems (SFSs) using the fully actuated system (FAS) approach, unlike previous research that primarily focuses on asymptotic stability control for such systems. First, the uncertain high-order SFSs are transformed into a high-order FAS. Next, a performance function is introduced to perform a coordinate transformation on the FAS, turning the original control problem into a boundedness issue for the transformed system. Then, neural networks are used to approximate the system’s uncertain terms, and a controller is designed for the transformed system based on the FAS approach. Using Lyapunov theory, it is proved that all signals in the closed-loop system are uniformly ultimately bounded, and the system output can converge to a specified region within a prescribed time. Finally, the effectiveness of the proposed control method is demonstrated through simulations of the RLC circuit system, a numerical example and an electromechanical system.
| Original language | English |
|---|---|
| Pages (from-to) | 6185-6194 |
| Number of pages | 10 |
| Journal | IEEE Transactions on Circuits and Systems |
| Volume | 72 |
| Issue number | 10 |
| DOIs | |
| State | Published - 2025 |
Keywords
- Fully actuated system approach
- high-order SFSs
- neural network approximation
- practical prescribed-time control
Fingerprint
Dive into the research topics of 'Practical Prescribed-Time Control for High-Order Strict-Feedback Systems Based on Fully Actuated System Approach'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver