Distributed State Estimation for Complex Networks with Periodic Inner Coupling and Mixed Sensors

The distributed state estimation for a set of complex networks with inner coupling changing periodically and hybrid sensors is investigated in this paper. A state predictor is devised on the basis of the model, where two sensors are used to measure the states. A random sequence following the Bernoulli distribution is employed to represent the selection of measurements. A distributed state estimator is contrived by utilizing the measurements. Then the prediction error and the estimation error are deduced. Furthermore, the optimal upper bound of the estimation error covariance is solved by contriving the optimal estimation gain. Eventually, a numerical instance is given to demonstrate the rationality of the distributed estimation.