Partial‐nodes‐based state estimation for state‐saturated complex networks with random mixed couplings under dynamic event‐triggered protocol

Abstract

The state estimation (SE) problem is addressed for state-saturated complex networks (CNs) contaminated by the random mixed couplings. Such coupling phenomenon consists of the random inner coupling and the random outer coupling, where the random inner coupling is reflected by multiplicative noise and the random outer coupling is described by random variable obeying uniform distribution. In order to reduce resource waste and calculation cost, the additional auxiliary variable method is employed to construct the dynamic event-triggered communication condition, which can more effectively represent the change of information demand. Accordingly, a novel partial-nodes-based (PNB) estimator is designed in the presence of general nonlinearity and state-saturated nonlinearity, which can estimate the whole states of network nodes with the aid of the measurement information from partial nodes. The appropriate estimator gain is obtained to ensure that the upper bound of estimation error covariance (UBEEC) is minimized. Moreover, sufficient condition is given to guarantee that the trace of the UBEEC is uniformly bounded. Finally, the numerical example is presented to demonstrate the feasibility and effectiveness of the developed PNB estimation algorithm.