Adaptive fault estimation for T-S fuzzy systems with unmeasurable premise variables
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Publication:1711752
DOI10.1186/s13662-018-1571-5zbMath1445.93020OpenAlexW2803290961WikidataQ130034262 ScholiaQ130034262MaRDI QIDQ1711752
Xiao-Jian Li, Shaokun Liu, Jingjing Yan, Heng Wang
Publication date: 18 January 2019
Published in: Advances in Difference Equations (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1186/s13662-018-1571-5
Fuzzy control/observation systems (93C42) Nonlinear systems in control theory (93C10) Estimation and detection in stochastic control theory (93E10)
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A study on input noise second-order filtering and smoothing of linear stochastic discrete systems with packet dropouts ⋮ Stability and performances synthesis of a class of Takagi–Sugeno systems with unmeasured premises: restricted-model-based approach
Cites Work
- Simultaneous fault detection and control for switched linear systems with mode-dependent average dwell-time
- Adaptive observers for TS fuzzy systems with unknown polynomial inputs
- Fault diagnosis of a class of nonlinear uncertain systems with Lipschitz nonlinearities using adaptive estimation
- Actuator and sensor faults estimation based on proportional integral observer for TS fuzzy model
- Nonlinear system fault diagnosis based on adaptive estimation
- \(\mathcal{H}_-/\mathcal{H}_\infty \) fault detection filter design for discrete-time Takagi-Sugeno fuzzy system
- Generalized \(H_2\) fault detection for two-dimensional Markovian jump systems
- Nonlinear robust fault reconstruction and estimation using a sliding mode observer
- Multi-objectiveH − ∕ H ∞ fault detection observer design for Takagi-Sugeno fuzzy systems with unmeasurable premise variables: descriptor approach
- Adaptive state feedback and tracking control of systems with actuator failures
- Fault diagnosis based on adaptive observer for a class of non-linear systems with unknown parameters
- Adaptive observer for multiple-input-multiple-output (MIMO) linear time-varying systems
- Residual Generation for Fault Diagnosis in Linear Time-Varying Systems
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