Event-based state estimation for time-varying stochastic coupling networks with missing measurements under uncertain occurrence probabilities

Abstract

This paper is concerned with the event-triggered state estimation problem for time-varying delayed complex networks with stochastic coupling and missing measurements under uncertain occurrence probabilities. The stochastic coupling and missing measurements are modeled by two set of mutually independent Bernoulli random variables, respectively, where the uncertainties of the occurrence probabilities are characterized. In addition, the event-triggered mechanism is employed to reduce the network burden during the data transmissions. The aim of the paper is to propose a robust state estimation method for addressed dynamics networks such that sufficient conditions are obtained to ensure the existence of an optimized upper bound of the estimation error covariance. Moreover, the monotonicity analysis between the trace of obtained upper bound of the estimation error covariance and the deterministic occurrence probability of the missing measurements is conducted. Finally, a numerical example is used to verify the validity of the proposed robust state estimation strategy.

Keywords:

• Stochastic coupling networks
• time-varying networks
• state estimation
• missing measurements
• uncertain occurrence probabilities

Notes

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China [grant number 61673141], [grant number 11301118], [grant number 61571168], [grant number 61703245]; the Fok Ying Tung Education Foundation of China [grant number 151004]; the University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province [grant number UNPYSCT-2016029]; the Postdoctoral Scientific Research Developmental Found of Heilongjiang Province of China [grant number LBH-Q16120]; the Science Funds for the Young Innovative Talents of HUST [grant number 201508]; the Alexander von Humboldt Foundation of Germany.