Name
Title | ||
|---|---|---|
Observer-Based Adaptive Neural Control For Non-Triangular Form Systems With Input Saturation And Full State Constraints |
Abstract | ||
|---|---|---|
This paper addresses the problem of adaptive output feedback control for a class of non-triangular time-varying delay system with input constraints and full-state constraints. A variable separation approach is adopted to overcome the design difficulty from the non-triangular structure. A novel Lyapunov function is introduced to compensate the time-delay terms. Unknown functions are approximated by the radial basis function neural networks. Only one parameter needs to be adjusted online, and a dynamic surface control technique is employed to reduce the computation burden. Combining the barrier Lyapunov function with a backstepping technique in the controller design procedure, the proposed controller guarantees that all the signals in the closed-loop system are uniformly ultimately bounded and the full-state constraints are met. The simulation results demonstrate the effectiveness of the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ACCESS.2018.2887073 | IEEE ACCESS |
Keywords | Field | DocType |
Adaptive neural control, non-triangular form systems, full state constraints, input saturation | Lyapunov function,Control theory,Backstepping,Nonlinear system,Computer science,Adaptive system,Control theory,Observer (quantum physics),Bounded function,Distributed computing,Computation | Journal |
Volume | ISSN | Citations |
7 | 2169-3536 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rui Zhang | 1 | 381 | 86.83 |
| Jun-Min LI | 2 | 390 | 36.09 |