Switched exponential state estimation and robust stability for interval neural networks with the average dwell time
Ning Li, Jinde Cao · IMA Journal of Mathematical Control and Information · 2013
This paper is concerned with the problem of the exponential state estimation for switched neural networks with uncertain parameters. Based on the theories of the switched systems and available output measurements, the mathematical model of the switched interval estimation error system under the switching rule with average dwell time is established. Multiple Lyapunov–Krasovskii functions are employed to ensure the stability of the switched estimation error system for all admissible time delays; both the existence conditions and the explicit characterization of the desired estimator are derived in terms of linear matrix inequalities. Moreover, the sufficient conditions for guaranteeing the robust exponential stability of switched interval neural networks with discrete and distributed time delays are easily derived. Finally, two numerical examples are provided to illustrate the validity of the theoretical results.