Robust Kalman Predictor for Descriptor System with Round-Robin Protocol and Deception Attacks

This paper presents a robust Kalman predictor for linear stochastic descriptor system with uncertain noise variances, Round-Robin protocol (RRP) and deception attacks. First, the original system is transformed to a standard system by applying singular value decomposition (SVD) method and the fictitious noise approach. A robust predictor is designed based on the RRP. Its actual prediction error variance guarantees a corresponding minimal upper bound for all allowable uncertainties and its robustness is proved by minimax estimation principle and Lyapunov equation method. A simulation example verifies the correctness and effectiveness of the proposed results.