Then with respect to fault reconstruction in the framework of fault tolerant control, an improved second-order sliding mode observer is constructed to estimate the thruster fault effect.
The aim of this paper is to deal with the problem of fault tolerant control in the framework of discrete event systems modeled as automata.
Furthermore, sufficient conditions for the existence of fault detector/controller are presented in the framework of linear matrix inequalities, and fault detector/controller gains and the supremum of quantizer range are derived by a convex optimized method.
In this paper the problem of Fault Tolerant Control (FTC) in the framework of Discrete Event Systems (DES) modeled as automata is considered.
Some properties of the generalized likelihood ratio (GLR) test for fault detection are discussed in the framework of linear regression with Gaussian noise.
This paper provides the description and presentation of a new actuator benchmark for fault diagnosis studies developed in the framework of the EC-funded Research Training Network DAMADICS.
The approach considers the application of a robust control technique to integrate the control design and the fault diagnosis in the same framework.
Furthermore, sufficient conditions for fault detection filter are given in the framework of linear matrix inequality, and the filter gains and the static quantizer range are obtained by a convex optimized problem.
Based on average dwell time (ADT) techniques, some new sufficient conditions for the existence of fault detection/controller unit are presented in the framework of linear matrix inequalities (LMIs) to ensure the control system has singular stochastic finite-time stability (SSFTS).
Then, based on the Lyapunov stability theory and the estimated fault parameters, some sufficient conditions for designing the adaptive robust H∞ fault-tolerant controller are presented in the framework of linear matrix inequalities (LMIs), which can guarantee that the closed-loop system is asymptotically stable and robust for both time-varying fault and exogenous disturbance.
The implementation of an additional observer allows for the reconstruction of the unknown inputs, which may be important in the framework of fault detection.
