IRI - Robust fault detection based on adaptive threshold generation using interval LPV observers

Publication

Robust fault detection based on adaptive threshold generation using interval LPV observers

Journal Article (2012)

Journal

International Journal of Adaptive Control and Signal Processing

Pages

258-283

Volume

Number

Doc link

http://dx.doi.org/10.1002/acs.1263

File

Download the digital copy of the doc pdf document

Authors

Montes de Oca, Saúl
Puig Cayuela, Vicenç
Blesa, Joaquim

Projects associated

WATMAN: Analysis and Design of distributed optimal control strategies applied to large-scale WATer systems MANagement

Abstract

In this paper, robust fault detection based on adaptive threshold generation of a non-linear system described by means of a linear parameter-varying (LPV) model is addressed. Adaptive threshold is generated using an interval LPV observer that generates a band of predicted outputs taking into account the parameter uncertainties bounded using intervals. An algorithm that propagates the uncertainty based on zonotopes is proposed. The design procedure of this interval LPV observer is implemented via pole placement using linear matrix inequalities. Finally, the minimum detectable fault is characterized using fault sensitivity analysis and residual uncertainty bounds. Two examples, one based on a quadruple-tank system and another based on a two-degree of freedom helicopter, are used to assess the validity of the proposed fault detection approach.

Author keywords

fault detection, linear parameter-varying, interval LPV observer, linear matrix inequalities, zonotopes, minimum detectable fault

Scientific reference

S. Montes, V. Puig and J. Blesa. Robust fault detection based on adaptive threshold generation using interval LPV observers. International Journal of Adaptive Control and Signal Processing, 26(3): 258-283, 2012.