Robust guaranteed cost control for time‐delay fractional‐order neural networks systems

Abstract

SummaryIn this paper, we investigate the problem of guaranteed cost control of uncertain fractional‐order neural networks systems with time delays. By employing the Lyapunov‐Razumikhin theorem, a sufficient condition for designing a state‐feedback controller which makes the closed‐loop system asymptotically stable and guarantees an adequate cost level of performance is derived in terms of bilinear matrix inequalities. Two numerical examples are given to show the effectiveness of the obtained results.