Protocol-Based State Estimation for 2-D Markov Jumping Systems With Randomly Occurring FDIAs
研究了二维马尔可夫跳变系统在随机虚假数据注入攻击下的状态估计问题，提出一种结合概率多区间事件触发协议和时变饱和机制的估计方法，并用粒子群优化算法调参，仿真验证了有效性。
This article investigates the state estimation problem for 2-D Markov jumping systems subjected to randomly occurring false data injection attack. To address this challenge, a novel probabilistic multi-interval ETP (PMIETP) is proposed, integrated with a time-varying saturation mechanism (TVSM). The PMIETP is designed by combining subinterval triggering thresholds with a probability distribution model, thereby enhancing system performance and adaptability under varying network conditions. To further mitigate the impact of maliciously injected data and improve estimation robustness, a TVSM-based estimator is developed, which employs an adaptive threshold to confine abnormal data within an acceptable range. In addition, a particle swarm optimization algorithm is employed to fine-tune design parameters, thereby reducing the conservativeness of linear matrix inequality conditions. Based on Lyapunov stability theory, sufficient criteria are derived to guarantee mean-square asymptotic stability and prescribed noise attenuation performance. Finally, a numerical simulation example demonstrates the effectiveness and superiorities of the proposed approach over existing methods.