A general matrix decomposition approach with application to stabilization of networked systems with stochastic sampling and two-channel deception attacks
Abstract
This study is concerned with the stabilization analysis and controller design for networked systems with stochastic sampling and two-channel deception attacks. First, we give a general matrix decomposition approach which is applicable to scenarios where the system matrix A$A$ contains complex-value eigenvalues. Then, a discrete stochastic framework is established for a class of networked systems which considers the joint effects of sampling errors and two-channel deception attacks. Utilizing the matrix decomposition approach introduced in this study, it becomes feasible to decouple the expectation operations for specific coupling matrices characterized by substantial nonlinearity and randomness. Based on this, a stabilization controller is constructed that ensures the exponential mean-square stability of the resulting discrete stochastic system. Finally, three simulation examples are provided to validate the effectiveness of the proposed approach. This study is concerned with the stabilization analysis and controller design for networked systems with stochastic sampling and two-channel deception attacks. A discrete stochastic framework is established for a class of networked systems which consider the joint effects of sampling errors and two-channel deception attacks. A general matrix decomposition is proposed to help with the stabilization analysis and controller design for the systems. image
