Exponential synchronization of uncertain chaotic inertial neural networks by guaranteed cost intermittent control

Abstract

This paper utilizes the guaranteed cost intermittent control to achieve exponential synchronization of uncertain chaotic inertial neural networks (UCINNs). Concretely, the second-order UCINNs are first transformed into the first-order neural network form by variable substitution. Then, under the new guaranteed cost intermittent lemma, the Lyapunov stability theory, as well as the designed intermittent controller, sufficient conditions in the form of linear matrix inequalities (LMIs) are derived to ensure exponential synchronization of UCINNs. Moreover, the optimal control gain and the upper bound of the cost function are obtained by introducing auxiliary variables. Lastly, numerical simulation confirms the viability and effectiveness of the proposed approach.