Toggle Main Menu Toggle Search

Open Access padlockePrints

State-space residual based monitoring

Lookup NU author(s): Ewan Mercer, Professor Elaine Martin, Emeritus Professor Julian Morris


Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Although the process performance monitoring tools of dynamic Principal Component Analysis (PCA) and Canonical Variate Analysis (CVA) take into account process dynamics, the monitoring statistics still contain serial correlation. Consequently the traditional statistical basis for the calculation of control limits will be invalid resulting in either missed out-of-control signals or an excess of false alarms. A methodology is proposed whereby a CVA state-space model is first developed and then a PCA based monitoring scheme is formed using the model mismatch. In this case, the residuals will be independent and identically distributed and the standard control limits will be valid. The methodology is demonstrated on the benchmark Tennessee Eastman problem. © 2002 Elsevier B.V. All rights reserved.

Publication metadata

Author(s): Mercer E, Martin E, Morris A

Editor(s): Johan Grievink and Jan van Schijndel

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Computer Aided Chemical Engineering

Year of Conference: 2002

Pages: 727-732

ISSN: 1570-7946

Publisher: Computer Aided Chemical Engineering: Elsevier BV


DOI: 10.1016/S1570-7946(02)80149-3

Library holdings: Search Newcastle University Library for this item

ISBN: 9780444511096