Event-triggered fault detection for T-S fuzzy systems with local nonlinear models in finite-frequency domain

Abstract

This article investigates the issue of event-triggered fault detection (FD) filter design for T-S fuzzy systems with local nonlinear models. A novel $H_{-}/H_{\mathrm{\infty }}$ FD filter subject to the event triggering transmission mechanism is designed in finite-frequency domain. Then, a novel lemma, in which the nonlinear part and the event triggering mechanism are dealt appropriately, is presented to capture the sensitivity and robustness performances. In addition, the slack matrices are utilised to derive optimal filter parameters by solving a convex optimisation problem. The less conservative FD method can get better detection performances than those entire-frequency methods. Finally, an example is introduced to verify the new results.

Keywords:

• T-S fuzzy nonlinear systems
• fault detection
• event-triggered mechanism
• finite-frequency domain
• linear matrix inequalities (LMIs)

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported in part by the Funds of the Natural Science Foundation of Liaoning Province of China [grant number 2019-ZD-0118].

Notes on contributors

Ying Gu

Ying Gu received the B.S. and M.S. degrees in mathematics from Northeast Normal University, China, in 2001 and 2005, respectively, and the Ph.D. degree in Control Theory and Engineering from Northeastern University, China, in 2018. Her research interests include fault detection, nonlinear systems and networked control systems.

Ming Huangfu

Ming Huangfu received the B.S. and M.S. degrees in mathematics from Heilongjiang University, China, in 2002 and 2005, respectively. Currently, he is pursuing the Ph.D. degree in mathematics from Dalian University of Technology, China. His research interests include stochastic optimisation and matrix optimisation.