Active fault tolerant control using state-space self-tuning control approach
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Publication:5438707
DOI10.1080/00207720600879625zbMath1129.93047OpenAlexW2087316571MaRDI QIDQ5438707
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Publication date: 28 January 2008
Published in: International Journal of Systems Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207720600879625
Filtering in stochastic control theory (93E11) Sensitivity (robustness) (93B35) Stochastic systems in control theory (general) (93E03)
Related Items (7)
A low-order active fault-tolerant state space self-tuner for the unknown sampled-data nonlinear singular system using OKID and modified ARMAX model-based system identification ⋮ Adaptive actuator failure compensation control of uncertain nonlinear systems with guaranteed transient performance ⋮ A novel on-line Observer/Kalman filter identification method and its application to input-constrained active fault-tolerant tracker design for unknown stochastic systems ⋮ An active fault-tolerant PWM tracker for unknown nonlinear stochastic hybrid systems: NARMAX model and OKID-based state-space self-tuning control ⋮ Realization of causal current output-based optimal full/reducedorder observer and tracker for the linear sampled-data system with a direct transmission term ⋮ Exponential stability andL2-gain analysis for a class of faulty systems ⋮ A novel on-line OCID method and its application to input-constrained active fault-tolerant tracker design for unknown nonlinear systems
Cites Work
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- A mixed \(\mathcal H_2/\mathcal H_{\infty}\) approach to simultaneous fault detection and control.
- Input-output modeling of nonlinear systems with time-varying linear models
- Transformations of a class of multivariable control systems to block companion forms
- Reconfigurable control system design via perfect model following
- Design of reconfigurable control systems using eigenstructure assignments
- Stability of the pseudo-inverse method for reconfigurable control systems
- Adaptive Fault-Tolerant Control of Nonlinear Uncertain Systems: An Information-Based Diagnostic Approach
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