Robust fault detection using Luenberger-type unknown input observers-a parametric approach

Abstract

A new parametric observer-based approach for robust fault detection in multivariable linear systems with unknown disturbances is proposed. The residual is generated through utilizing a Luenberger function observer. By using a parametric solution to a class of generalized Sylvester matrix equations, a parametrization is proposed for the residual generator on the basis of a Luenberger function observer. By further properly constraining the design parameters provided in the Luenberger observer design, the eVect of the unknown disturbance is decoupled from the residual signal. The proposed approach provides all the degrees of freedom and is demonstrated to be simple and eVective.

Detection and isolation of false data injection attack for smart grids via unknown input observers

“…The detailed proof of condition (29) can be seen in [35]. Condition (29) ensures that the residuals generated by UIO are sensitive to the cyber attack.…”

Adaptive Sliding Mode Observer‐Based Robust Fault Reconstruction for a Helicopter With Actuator Fault

“…Among them, observer-based approaches have been used widely, such as adaptive observer [9,10], unknown input observer [11][12][13][14], sliding mode observer [15][16][17], adaptive sliding mode observer [18][19][20][21], and robust observer [22].…”

Explicit and Iterative Methods for Solving the Matrix Equation AV + BW = EVF + C

“…When dealing with complicated linear systems, such as large scale systems with interconnections [2], linear systems with certain partitioned structure or extended modules, and linear systems with input constraints [3] we sometimes naturally encounter matrix equations (1). The generalized Sylvester matrix equations (1) have very wide application in many problems such as pole/eigenstructure assignment design [4,5], observer design [6], and robust fault detection [7][8][9]. Niu et al [13] proposed a relaxed gradient based iterative algorithm for solving Sylvester equations AX + XB = C. In [14] a numerical solution to the problem of eigenstructure assignment for descriptor systems is investigated and a numerical solution of the generalized Sylvester matrix equation AV + BW = EVE using an iterative method.…”

“…k k ¼ 1:0000e À 004 Remark 1. Since the considered generalized Sylvester matrix equations (1) have very wide application in many problems such as pole/Eigen structure assignment design [4,5], observer design [6] and robust fault detection [7][8][9] it was worthwhile to consider its solution.…”