Robust and optimal control
Robust Solutions to Least-Squares Problems with Uncertain Data
SIAM Journal on Matrix Analysis and Applications
Brief paper: Disturbance decoupling in fault detection of linear periodic systems
Automatica (Journal of IFAC)
Computation of a reference model for robust fault detection and isolation residual generation
Journal of Control Science and Engineering - Robustness Issues in Fault Diagnosis and Fault Tolerant Control
Optimal robust fault detection for linear discrete time systems
Journal of Control Science and Engineering - Robustness Issues in Fault Diagnosis and Fault Tolerant Control
On fault detection in linear discrete-time, periodic, and sampled-data systems
Journal of Control Science and Engineering - Robustness Issues in Fault Diagnosis and Fault Tolerant Control
Parity space-based fault detection for Markovian jump systems
International Journal of Systems Science
A matrix factorization solution to the H-/H∞ fault detection problem
Automatica (Journal of IFAC)
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
Brief An LMI approach to design robust fault detection filter for uncertain LTI systems
Automatica (Journal of IFAC)
Brief Robust fault detection in uncertain dynamic systems
Automatica (Journal of IFAC)
Hi-index | 22.14 |
This work proposes a robust fault detection and isolation (FDI) scheme for linear discrete-time systems subject to faults, bounded additive disturbances and norm-bounded structured uncertainties. FDI is achieved by computing, on-line, upper and lower bounds on the fault signal such that a fault is regarded as having occurred when its upper bound is smaller than zero or lower bound is larger than zero. Linear Matrix Inequality (LMI) optimization techniques are used to obtain the bounds. Furthermore, a subsequent-state-estimation technique, together with an estimation horizon update procedure, is proposed, which allows the on-line FDI process to be repeated in a moving horizon procedure. The approach is also extended to solve the fault detection (FD) problem of obtaining lower bounds on the total fault signal energy within the estimation horizon. The scheme gives the best estimates of the fault signals given the information available and is sufficiently flexible to incorporate other information that may be available, such as bounds on the disturbance energy. Thus our scheme is immune to false alarms if the system and disturbance are within the uncertainty description. Moreover, we propose a new robustness result to obtain the bounds, which is an extension of current techniques for handling model uncertainties. Finally, the approach is verified using two numerical examples.