Event-triggered Distributed Filtering for a Class of Uncertain Parameter Systems over Dynamic Switching Topologies Networks Subject to Missing Measurements.

In this paper, the event-triggered distributed filtering (ETDF) problem is discussed for a class of uncertain parameter systems over dynamic switching topologies networks subject to missing measurements. The event-triggered communication mechanism is introduced to improve energy utilization of sensor network. The randomness phenomena of dynamic switching typologies and missing measurements are characterized by two sets of random variables satisfying Bernoulli distribution. By taking the influence of the parameter uncertainty of the system and the stochastic disturbance of the corresponding estimator gain into account, a novel optimal ETDF is constructed with a linear consistency strategy. Moreover, the estimator gain is obtained by minimizing the upper bound of the estimation error covariance. Finally, an illustrative simulation is provided to illustrate the effectiveness of the proposed algorithm.