IRI - Robust identification and fault diagnosis based on uncertain multiple input-multiple output linear parameter varying parity equations and zonotopes

Publication

Robust identification and fault diagnosis based on uncertain multiple input-multiple output linear parameter varying parity equations and zonotopes

Journal Article (2012)

Journal

Journal of Process Control

Pages

1890-1912

Volume

Number

Doc link

http://dx.doi.org/10.1016/j.jprocont.2012.09.007

File

Download the digital copy of the doc pdf document

Authors

Blesa, Joaquim
Puig Cayuela, Vicenç
Saludes Closa, Jordi

Projects associated

WATMAN: Analysis and Design of distributed optimal control strategies applied to large-scale WATer systems MANagement
EFFINET: EFFicient Integrated real-time monitoring and control of drinking water NETworks

Abstract

We present a robust fault diagnosis method for uncertain multiple input-multiple output (MIMO) linear parameter varying (LPV) parity equations. The fault detection methodology is based on checking whether measurements are inside the prediction bounds provided by the uncertain MIMO LPV parity equations. The proposed approach takes into account existing couplings between the different measured outputs. Modelling and prediction uncertainty bounds are computed using zonotopes. Also proposed is an identification algorithm that estimates model parameters and their uncertainty such that all measured data free of faults will be inside the predicted bounds. The fault isolation and estimation algorithm is based on the use of residual fault sensitivity. Finally, two case studies (one based on a water distribution network and the other on a four-tank system) illustrate the effectiveness of the proposed approach.

Author keywords

fault detection, isolation and estimation, linear parameter varying model, sensitivity matrix

Scientific reference

J. Blesa, V. Puig and J. Saludes. Robust identification and fault diagnosis based on uncertain multiple input-multiple output linear parameter varying parity equations and zonotopes. Journal of Process Control, 22(10): 1890-1912, 2012.