Name
Title | ||
|---|---|---|
Adaptive Control Based Particle Swarm Optimization And Chebyshev Neural Network For Chaotic Systems |
Abstract | ||
|---|---|---|
The control approach for chaotic systems is one of the hottest research topics in nonlinear area. This paper is concerned with the controller design problem for chaotic systems. The particle swarm optimization (PSO) algorithm is firstly proposed to search for the weights of the Chebyshev neural networks (CNNs), and then an adaptive controller for the chaotic systems is designed based on the PSO and CNNs. Moreover, it is proved that the designed controller can guarantee the stability of chaotic systems. Numeral simulation shows the effectiveness of the proposed method in the Logistic chaotic system. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.4304/jcp.9.6.1385-1390 | JOURNAL OF COMPUTERS |
Keywords | Field | DocType |
adaptive control, particle swarm optimization, Chebyshev neural networks, chaotic systems | Particle swarm optimization,Control theory,Nonlinear system,Computer science,Control theory,Chaotic systems,Chebyshev filter,Adaptive control,Artificial neural network,Chaotic | Journal |
Volume | Issue | ISSN |
9 | 6 | 1796-203X |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
3 | ||