A sum-based discrete event-triggered dynamic output feedback control for interval type-2 fuzzy systems

Duo Zhang; Liruo Zhang; Zhongjing Yu; Lan Shu; Akshya Kumar Swain

doi:10.1016/j.isatra.2021.12.031

A sum-based discrete event-triggered dynamic output feedback control for interval type-2 fuzzy systems

ISA Trans. 2022 Oct;129(Pt A):44-55. doi: 10.1016/j.isatra.2021.12.031. Epub 2021 Dec 28.

Authors

Duo Zhang¹, Liruo Zhang², Zhongjing Yu³, Lan Shu⁴, Akshya Kumar Swain⁵

Affiliations

¹ School of Mathematical Sciences, University of Electronic Science and Technology of China, Sichuan 611731, China. Electronic address: duozhang92@std.uestc.edu.cn.
² Department of Electrical, Computer and Software Engineering, the University of Auckland, Auckland 1142, New Zealand. Electronic address: lzha711@aucklanduni.ac.nz.
³ Data Ming Lab, School of Computer Sciences and Engineering, University of Electronic Science and Technology of China, Sichuan 611731, China. Electronic address: zhongjing.yu@outlook.com.
⁴ School of Mathematical Sciences, University of Electronic Science and Technology of China, Sichuan 611731, China. Electronic address: shul@uestc.edu.cn.
⁵ Department of Electrical, Computer and Software Engineering, the University of Auckland, Auckland 1142, New Zealand. Electronic address: a.swain@auckland.ac.nz.

PMID: 35016801
DOI: 10.1016/j.isatra.2021.12.031

Abstract

The current study concentrates on the event-based controller design for nonlinear networked systems characterized by the interval type-2 (IT2) fuzzy model. An innovative sum-based discrete event-triggered mechanism (SDETM), whose triggering condition includes several previous measurement samples, is proposed. Compared to the traditional event-triggered mechanism (ETM), the novel SDETM requires less network resources consumption. A dynamic output feedback controller (DOFC) is designed to achieve stability of the system. A novel stability criteria is established via the Lyapunov-Krasovskii functional method with the prescribed H_∞ performance. Co-design of the DOFC and SDETM parameters is carried out using the cone complimentarity linearization (CCL) algorithm. The effectiveness of the proposed method is demonstrated with two practical cases.

Keywords: Cone-complimentarity linearization algorithm; Dynamic output feedback; Interval type-2 fuzzy model; Sum-based discrete event-triggered mechanism.