An H/sub ∞/ filtering approach to robust detection of failures in dynamical systems

Abstract

Along the lines of the rerent results on H , output estimation theory this paper deals with the problem of designing robust det~ert.iuir filters in a ront,iniioiis-tiine setting for detecting failures i n uiirert.aiii dynamical systems where methods for decoupling of t,he fault etfrct.s from system perturbations arc not available. Through the appropriate choice of the filter gain a tradeoff is made between the effect of worst-case disturbance and Lz norm of the filter error

Solving of the Modified Filter Algebraic Riccati Equation for H-infinity fault detection filtering

“…It has to be noted, that this method is often referred to, see e.g. in [1], [2] and [20], [21], but we have not found any algorithm about it. This has been the motivation for its description.…”

“…This method requires the solution of a linear-quadratic optimization problem that leads to the solution of the Modified Filter Algebraic Riccati Equation (MFARE), see e.g. in [1], [2], [3] and [4].…”

A Congestion Detection Based Traffic Control for Signalized Intersection

“…This kind of modification means the reconfiguration of the whole system. Fault detection aims to recognize the errors by considering disturbance impacts as well [3,4,6,14]. …”

Robust Residual Generation for Diagnosis Including a Reference Model for Residual Behavior

“…This problem is well studied and there exists many papers with different design focuses on the subject, e.g. (Frank and Ding, 1994;Mangoubi et al, 1995;Edelmayer et al, 1994;Mangoubi et al, 1994;Mangoubi et al, 1992;Eich and Oehler, 1997;Patton and Chen, 1993). Here, focus is on designing robust residual generators, dealing with model uncertainty, to fit in a structured residuals framework.…”