Partial-Nodes-Based State Estimation for Stochastic Coupled Complex Networks with Random Sensor Delay: An Event-Triggered Communication Method.

The partial-nodes-based state estimation (PNBSE) problem is investigated for discrete time-varying nonlinear complex networks subject to stochastic inner coupling strength (SICS) and random sensor delay. The SICS is described by multiplicative noise. The random sensor delay with uncertain occurrence probability is modeled by a sequence of random variables, which is governed by Bernoulli distribution. For the sake of reducing the network transmission burden, a novel state estimator is constructed based on an event-triggered communication mechanism. By means of solving two recursive matrix equations, the upper bound of estimation error covariance (UBEEC) is calculated, and the appropriate gain matrix is selected to minimize the obtained UBEEC. Furthermore, the performance of the proposed estimation algorithm is verified, where the monotonicity analysis is shown between the trace of UBEEC and the occurrence probability of random sensor delay. Conclusively, a simulation example is adopted to illustrate the feasibility of PNBSE method. [ABSTRACT FROM AUTHOR]