Robust control of a class of neural networks with bounded uncertainties and time-varying delays
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 CohenGrossberg 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.
variable structure control cohengrossberg neural networks cellular neural networks hopfield neural networks