Fixed-Time Adaptive Fuzzy Control for Uncertain Nonlinear Systems
| Autor: | C. L. Philip Chen, Kaixin Lu, Yaonan Wang, Zhi Liu |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Current (mathematics)
Computer science Applied Mathematics Stability (learning theory) 02 engineering and technology Interval (mathematics) Fuzzy control system System dynamics Tracking error Nonlinear system Computational Theory and Mathematics Artificial Intelligence Control and Systems Engineering Control theory 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Adaptation (computer science) |
| Zdroj: | IEEE Transactions on Fuzzy Systems. 29:3769-3781 |
| ISSN: | 1941-0034 1063-6706 |
| DOI: | 10.1109/tfuzz.2020.3028458 |
| Popis: | Most current methodologies on fixed-time adaptive fuzzy control for uncertain nonlinear systems result in practical fixed-time stability but not fixed-time stability, or require prior knowledge of the system dynamics. To obviate such restrictions, a fixed-time adaptive fuzzy control scheme is newly proposed with the discoveries of a singularity-avoidance virtual control design, a modified class of tuning functions and a projection operator-based adaptation mechanism. Fixed-time stability is established in the sense that the tracking error asymptotically converges to a user-defined interval within a prescribed fixed time. Illustrative examples verify the approaches developed. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|