Resilient State and Fault Estimation for Stochastic Coupled Complex Networks with Randomly Occurring Faults under Hybrid Attacks

This paper investigates the recursive distributed resilient state and fault estimation (SFE) problem for time-varying complex networks (CNs) affected by stochastic coupling strength (SCS) and randomly occurring faults (ROFs) under hybrid attacks. The coupling strength between nodes adheres to a uniform distribution, and the randomness of faults occurrences is modeled using Bernoulli-distributed random variables. A hybrid cyberattack model is employed to represent both intermittent denial-of-service attacks and deception attacks. Additionally, the perturbations in the estimator gain matrix are modeled as a set of zero-mean multiplicative noise. The main purpose of this paper is to develop a time-varying estimator for concurrent estimation of system states and fault signals. The estimator ensures that, under the influence of SCS, ROFs, and hybrid attacks, the estimation error covariance (EEC) stays within an upper bound (UB), which is minimized in real time by dynamically adjusting the estimator gains. Finally, a numerical simulation is conducted to evaluate the effectiveness of the proposed recursive state and fault estimation algorithm.