H Infinity Control of Switching Delayed Stochastic Hopfield Neural Network Systems with Markovian Jumping Parameters

This paper considers the problem of H infin control of a class of Hopfield neural network systems with time-varying delays and Markovian jumping parameters. The delays are assumed to be bounded. The jumping parameters considered here are generated from a continuous-time discrete-state homogenous Mar...

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Bibliographic Details
Main Authors: Xiaole Xu, Lixin Gao, Haiwa Guan
Format: Conference Proceeding
Language:English
Subjects:
Control systems
delay
Delay systems
H infinity control
Hopfield neural networks
Markov processes
Markovian
neural network
Stability
State feedback
State-space methods
Stochastic systems
Switching systems
Time varying systems
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Summary:This paper considers the problem of H infin control of a class of Hopfield neural network systems with time-varying delays and Markovian jumping parameters. The delays are assumed to be bounded. The jumping parameters considered here are generated from a continuous-time discrete-state homogenous Markov process, which are governed by a Markov process with discrete and finite state space. Our purpose is to design state feedback controllers that guarantee the systems are stochastic stability with a prescribed performance. Based on the Lyapunov method and stochastic analysis approach, a sufficient condition for the solvability of the problems are derived in term of linear matrix inequalities, which can be easily checked by resorting to available software packages. A numerical example is exploited to demonstrate the effectiveness of the proposed results.
DOI:10.1109/ICICTA.2008.386