Name
Title | ||
|---|---|---|
Adaptive finite-time fuzzy control of full-state constrained high-order nonlinear systems without feasibility conditions and its application |
Abstract | ||
|---|---|---|
This paper investigates adaptive finite-time fuzzy control for full-state constrained high-order nonlinear systems. Fuzzy logic systems are employed to relax growth assumptions imposed on unknown system nonlinearities. By integrating a nonlinear state-dependent transformation into control design, full-state constraints can be handled without imposing feasibility conditions on virtual controllers. It is rigorously proved that fuzzy approximation is valid based on a compact set, full-state constraints aren’t violated for all time. Besides, the solution of the closed-loop system is semi-global practical finite-time stable, and the tracking error converges to an adjustable compact set around the origin in finite-time. Two examples show the advantages of this control scheme. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.neucom.2020.02.089 | Neurocomputing |
Keywords | DocType | Volume |
High-order nonlinear systems,Full-state constraints,Adaptive finite-time fuzzy control,Feasibility conditions | Journal | 399 |
ISSN | Citations | PageRank |
0925-2312 | 3 | 0.36 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| You Wu | 1 | 39 | 3.83 |
| Ruiming Xie | 2 | 3 | 1.37 |
| Xuejun Xie | 3 | 65 | 5.91 |