Robust control of a class of neural networks with bounded uncertainties and time-varying delays
| Autor: | Chao-Jung Cheng |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Variable structure control
Time delay neural network Hopfield neural networks Cellular neural networks Computational Mathematics Recurrent neural network Computational Theory and Mathematics Control theory Modeling and Simulation Cellular neural network Modelling and Simulation Cohen–Grossberg neural networks Feedforward neural network Robust control Intelligent control Stochastic neural network Mathematics |
| Zdroj: | Computers & Mathematics with Applications. 56(5):1245-1254 |
| ISSN: | 0898-1221 |
| DOI: | 10.1016/j.camwa.2008.03.012 |
| Popis: | This paper investigates the robust control problem for a class of neural networks subject to bounded uncertainties and time-varying delays. A memoryless decentralized variable structure control law with dead-zone input for guaranteeing global asymptotical system stability is derived. The results demonstrate that the derived control law does not restrict the derivative of the time-varying delays even if dead-zone nonlinearity occurs in the control input. Such a control law can be used to stabilize Cohen–Grossberg neural networks, cellular neural networks and Hopfield neural networks; all of which have bounded uncertainties and time-varying delays. Two examples are provided to illustrate the effectiveness and validity of the proposed control scheme. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect