Event-triggered fault detection for T-S fuzzy systems with local nonlinear models in finite-frequency domain
Ying Gu, Huangfu Ming
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∞ 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.
Topics & Concepts
Robustness (evolution)Nonlinear systemControl theory (sociology)Fault detection and isolationFilter (signal processing)Frequency domainFuzzy logicComputer scienceMathematicsArtificial intelligenceBiochemistryGeneQuantum mechanicsPhysicsComputer visionControl (management)ChemistryFault Detection and Control SystemsStability and Control of Uncertain SystemsNeural Networks Stability and Synchronization