Name
Title | ||
|---|---|---|
Hybrid adaptive control based on a Hopfield dynamic neural network for nonlinear dynamical systems |
Abstract | ||
|---|---|---|
In this paper, we propose a hybrid adaptive control scheme based on Hopfield-based dynamic neural network (HACHNN) for SISO nonlinear systems. An auxiliary direct adaptive controller is proposed to ensure the stability in the time-interval of when an indirect adaptive controller is failed because of ĝ(x)→0. The weights of the Hopfield-based dynamic neural network are on-line tuned by the adaptive laws derived in the sense of Lyapunov theorem, so that the stability of the closed-loop system can be guaranteed, and all signals in the closed-loop system are bounded. The designed structure of the Hopfield-based dynamic neural network maintains the tracking performance of the control scheme, and it also makes the practical implementation much easier. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IJCNN.2012.6252454 | Neural Networks |
Keywords | Field | DocType |
Hopfield neural nets,Lyapunov methods,adaptive control,closed loop systems,control system analysis,nonlinear dynamical systems,HACHNN,Hopfield-based dynamic neural network,Lyapunov theorem,SISO nonlinear systems,adaptive laws,auxiliary direct adaptive controller,closed-loop system,hybrid adaptive control scheme,indirect adaptive controller,nonlinear dynamical systems,tracking performance,Hopfield dynamic neural network,hybrid adaptive control scheme | Control theory,Nonlinear system,Computer science,Control theory,Nonlinear dynamical systems,Lyapunov theorem,Adaptive control,Dynamic neural network,Hopfield network,Bounded function | Conference |
ISSN | ISBN | Citations |
2161-4393 E-ISBN : 978-1-4673-1489-3 | 978-1-4673-1489-3 | 0 |
PageRank | References | Authors |
0.34 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| I.-Hsum Li | 1 | 59 | 7.82 |
| Lian-Wang Lee | 2 | 26 | 6.33 |
| Wei-Yen Wang | 3 | 995 | 87.40 |