Optimization and stabilization of networked control systems: An Estimation of Distribution Algorithm approach

This paper addresses the optimization and stabilization problem for networked control systems (NCSs). The memoryless state feedback controller is considered, and the resulting closed-loop NCS is modeled as a discrete-time switch system. By defining a state-dependent Lyapunov function, the stability conditions are derived for NCSs in terms of linear matrix inequalities (LMIs). Based on the obtained stability conditions, the corresponding controller design problem is solved, and estimation of distribution algorithm (EDA) is used to select the optimal state feedback stabilizing gain. It is shown that the proposed method can be easily implemented to various applications, since it is simple and has no assumptions on time delays and packet losses. Simulation results are given to demonstrate the effectiveness of the proposed approach.