Robust fault estimation based on learning observer for Takagi‐Sugeno fuzzy systems with interval time‐varying delay

DOI10.1002/acs.3070zbMath1451.93080OpenAlexW2984700882WikidataQ126767685 ScholiaQ126767685MaRDI QIDQ5128878

Kuo Tian, Shiya Cheng, Fuqiang You, Xin-yan Zhang

Publication date: 26 October 2020

Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/acs.3070

zbMATH Keywords

linear matrix inequalities (LMIs)robust fault estimationlearning observerTakagi-sugeno (T-S) fuzzy systems

Mathematics Subject Classification ID

Sensitivity (robustness) (93B35) Fuzzy control/observation systems (93C42) Delay control/observation systems (93C43) Observers (93B53)

Related Items (4)

On the state estimation for nonlinear continuous-time fuzzy systems ⋮ Limited‐information learning observer for simultaneous estimation of states and parameters ⋮ Unknown input observers for time-varying delay Takagi-Sugeno fuzzy systems with unmeasured nonlinear consequents ⋮ An observer design for Takagi-Sugeno fuzzy bilinear control systems

Cites Work

• Robust fast adaptive fault estimation for systems with time-varying interval delay
• \(H_\infty\) filtering for T-S fuzzy systems with multiple time-varying delays: an improved delays-dependent region partitioning method
• Fault reconstruction for Takagi–Sugeno fuzzy systems via learning observers
• Integrated design of fault reconstruction and fault-tolerant control against actuator faults using learning observers
• Optimization based on quasi-Monte Carlo sampling to design state estimators for non-linear systems
• Set-based fault detection and isolation for detectable linear parameter-varying systems
• Fault detection and isolation for uncertain closed-loop systems based on adaptive and switching approaches
• Observer‐based fault estimators using iterative learning scheme for nonlinear time‐delay systems with intermittent faults
• Fault estimation for discrete-time switched nonlinear systems with discrete and distributed delays
• Robust fast adaptive fault estimation and tolerant control for T-S fuzzy systems with interval time-varying delay
• Robust fault reconstruction via learning observers in linear parameter‐varying systems subject to loss of actuator effectiveness

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