Protocol-Based State Estimation for Complex Networks With Nonhomogeneous Sojourn Probabilities

In this study, the partial-node-based state estimator design problem is addressed for complex networks subject to sojourn probabilities and a memory-based dynamic event-triggered protocol (DETP). Based on nonhomogeneous sojourn probabilities, a new switching law is presented to describe the dynamic behavior of the network topology, where the deterministic switching signal regulates the proper feedback sojourn probability information. Using historically transmitted packets, a novel memory-based DETP in the discrete-time domain was built simultaneously to alleviate energy consumption and improve system performance. On the basis of Lyapunov theory, the augmented dynamics are stochastically stable in the presence of a preset performance level. To this end, two simulation examples were presented to verify the validity and applicability of the developed methodology.