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Reachable set estimation for Markovian jump neural networks with time-varying delay
Wen-Juan Lin1, Yong He1, Min Wu1
1School of Automation, China University of Geosciences, Wuhan 430074, China; Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China.
Abstract:
This paper is concerned with the reachable set estimation for Markovian jump neural networks with time-varying delay and bounded peak inputs. The objective is to find a description of a reachable set that is containing all reachable states starting from the origin. In the framework of Lyapunov-Krasovskii functional method, an appropriate Lyapunov-Krasovskii functional is constructed firstly. Then by using the Wirtinger-based integral inequality and the extended reciprocally convex matrix inequality, an ellipsoidal description of the reachable set for the considered neural networks is derived. Finally, a numerical example with simulation results is provided to verify the effectiveness of our results.
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