State Estimation Of Networked Systems Subject To Cyberattacks

With the rapid development of communication technology,it has been easy to connect multiple devices by networks,and the systems that exchange data through networks continue to emerge.While the networks bring convenience,they also have some disadvantages,as data transmitted over networks is vulnerable to cyberattacks.Some states of complex system are difficult to be observed directly in reality and state estimation requires measurements of sensors.When the measurements or estimations are transmitted over networks,it is inevitably affected by the networks,which increases the complexity of state estimation.This article focuses on the problem of state estimation for networked systems whose transmission under deception attacks.It proposes a method of saturation to resist the impact of deception attacks.The main contents of this work are as follows:Firstly,for a class of systems with distributed time delays,a distributed estimator is designed based on an event-triggered mechanism.The estimator considers the impact of deception attacks on measurements transmitted over a network.After calculating the innovations by the received measurements,the estimator performs saturation to resist the effects of deception attacks.Suitable Lyapunov-Krasovskii functionals are constructed based on the distributed time delays,and the boundedness analysis is carried out in the mean square sense.The gains of estimators are also designed.Numerical simulations are conducted to verify the correctness of the theoretical results.Secondly,for a class of switching systems with nonlinearities and time-varying delay,which follow the persistent dwell-time regularity,the effects of deception attacks on transmissions of measurements are considered,and an estimator with innovation saturation is designed.Suitable Lyapunov-Krasovskii functionals are selected,and sufficient stability conditions are derived by using inequalities.The gains of estimator are obtained by solving linear matrix inequalities,and numerical simulations are conducted to validate the theoretical results.Finally,for a class of Markov jump systems with randomly occurring nonlinearity,considering the impact of communication delays on data transmission between estimators,and the impact of deception attacks on the received data from neighboring nodes,distributed estimators are designed.The estimator uses saturated innovations to mitigate the effects of deception attacks.Suitable Lyapunov-Krasovskii functionals are chosen for finite time H_∞performance analysis,and the gains of estimators are designed.The correctness of the theoretical results is verified through numerical simulations.