Event-Triggered Set-Membership State Estimation for Complex Networks: A Zonotopes-Based Method
Zhongyi Zhao, Zidong Wang, Lei Zou, Yun Chen, Weiguo Sheng
Abstract
This paper studies the set-membership state estimation (SMSE) problem for a class of complex networks under the event-triggered mechanism, where the external unknown-but-bounded (UBB) noises reside within a sequence of zonotopes. For the purpose of saving energy and reducing transmission burden, an event-triggered mechanism is employed for each node of the complex networks to schedule the signal transmissions between the nodes and the remote estimator. The aim of this paper is to design a set-membership estimator such that, in the presence of the UBB noises and the event-triggered scheduling scheme, the resultant estimation error is restrained into a set of zonotopes. According to the properties of zonotopes, a set of zonotopes confining the estimation error is first obtained by using the mathematical induction approach, and then the desired estimator parameters are recursively calculated by minimizing the <inline-formula><tex-math notation="LaTeX">$F$</tex-math></inline-formula>-radii of such a zonotopic set. Finally, the effectiveness of the proposed zonotopic SMSE algorithm is demonstrated through an illustrative example.