Observer-Based Asynchronous Stabilization for Networked Systems with Multichannel Attacks and Applications

In this study, the observer-based asynchronous stabilization is addressed for networked system under multichannel attacks, in which the asynchronous phenomenon refers to the mismatch between the controller mode and the actual attack mode. To accurately depict complex attack behaviors, a piecewise homogeneous semi-Markov chain (SMC) model modulated by a superstratum Markov chain is introduced, which can simultaneously describe the randomness of attack mode transitions and the time-varying nature of transition probabilities. Considering that the actual attack modes are inaccessible, an observer-based mode switching delay technique is designed to solve this challenge. Under the framework of a piecewise homogeneous SMC, a sufficient criterion is established to ensure the $\varsigma $ -error mean-square stability under random multichannel denial-of-service attacks by means of a Lyapunov function depending on observed attack modes, piecewise homogeneous variables, and elapsed time. Moreover, matrix decoupling and convexification techniques are employed to reduce the computational complexity. Finally, the effectiveness of the proposed method is demonstrated through two practical simulation cases.