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\(H_\infty \) State Estimation for Round-Robin Protocol-Based Markovian Jumping Neural Networks with Mixed Time Delays

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Abstract

This paper discusses the \(H_\infty \) state estimation issue in regard to Markovian jumping neural networks (MJNNs) under the scheduling of the Round-Robin protocol (RRP). The model takes into account mixed time-delays, sensor nonlinearities and exogenous disturbances, making it relatively general and comprehensive. The transmission of MJNNs signals invoked a communication scheme in which the RRP is used for the data transmissions in order to avoid undesirable data collisions. Protocol-dependent state estimator modeling of a hybrid switching system with mixed time delays and disturbances is designed for the first time to achieve asymptotic tracing for the neuron state. Using the Lyapunov stability theory and several asymptotic methods, sufficient conditions for guaranteeing the asymptotic stability of the state estimation are established under the constraint of \(H_\infty \) performance. By employing a combination of matrix analysis techniques, the estimator gain matrices are calculated by the feasible solutions to the linear matrix inequalities (LMIs). Finally, a numerical example and related simulations demonstrate the validity of the proposed model.

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Acknowledgements

The authors would like to express their sincere thanks to the Editor and anonymous reviewers for their helpful comments and suggestions. This work was supported in part by the Natural Science Foundation of Chongqing Municipality of China under Grant cstc2019jcyj-msxmX0722; in part by the Group Building Scientific Innovation Project for universities in Chongqing under Grant CXQT21021; in part by the Team Building Project for Graduate Tutors in Chongqing under Grant JDDSTD201802; in part by the Science and Technology Research Program of Chongqing Municipal Education Commission under Grant KJQN201900701, and in part by the Research and Innovation Program for Graduate Students in Chongqing Jiaotong University under Grant 2020S0056.

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  1. The School of Mathematics and Statistics, Chongqing Jiaotong University, Chongqing, 400074, China

    Cong Zou, Bing Li, Shishi Du & Xiaofeng Chen

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  1. Cong Zou
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  2. Bing Li
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Correspondence to Bing Li.

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Zou, C., Li, B., Du, S. et al. \(H_\infty \) State Estimation for Round-Robin Protocol-Based Markovian Jumping Neural Networks with Mixed Time Delays. Neural Process Lett 53, 4313–4330 (2021). https://doi.org/10.1007/s11063-021-10598-4

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