Fuzzy filtering based on decentralized adaptive event-triggered scheme for networked interconnected systems

This paper focuses on the problem of the fuzzy filtering for networked nonlinear interconnected systems based on decentralized adaptive event-triggered (AET) scheme. Firstly, a new decentralized AET scheme is proposed, and some unnecessary data packets are discarded through decentralized adaptive rule, thereby saving network communication resources. Secondly, the H infinity performance analysis of the filter error system is presented by using the fuzzy line-integral method, which does not need to give the time derivative upper bounds of the membership function in advance. Then, the combination of the Wirtinger-based inequality and the extended reciprocally convex matrix inequality is used to establish sufficient conditions for the filter error system to meet H infinity performance. Moreover, a method for jointly designing the distributed AET parameters and fuzzy filter parameters is proposed. Finally, two examples are given to verify the effectiveness of the proposed method. (c) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved. Superscript/Subscript Available

Automated summary

This paper proposes a new decentralized adaptive event-triggered scheme and introduces a method for H infinity performance analysis of filter error system using fuzzy line-integral method. The sufficient conditions for meeting H infinity performance of the filter error system are established through the combination of Wirtinger-based inequality and extended reciprocally convex matrix inequality.