Data-driven adaptive model-based predictive control with application in wastewater systems

This study is concerned with the development of a new data-driven adaptive model-based predictive controller (MBPC) with input constraints. The proposed methods employ subspace identification technique and a singular value decomposition (SVD)-based optimisation strategy to formulate the control algo...

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Main Authors: Abd. Wahab, Norhaliza, Katebi, R., Balderud, J., Rahmat, M. F.
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出版: The Institution of Engineering and Technology 2011
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spelling my.utm.448322017-01-31T06:21:54Z http://eprints.utm.my/id/eprint/44832/ Data-driven adaptive model-based predictive control with application in wastewater systems Abd. Wahab, Norhaliza Katebi, R. Balderud, J. Rahmat, M. F. TD Environmental technology. Sanitary engineering This study is concerned with the development of a new data-driven adaptive model-based predictive controller (MBPC) with input constraints. The proposed methods employ subspace identification technique and a singular value decomposition (SVD)-based optimisation strategy to formulate the control algorithm and incorporate the input constraints. Both direct adaptive model-based predictive controller (DAMBPC) and indirect adaptive model-based predictive controller (IAMBPC) are considered. In DAMBPC, the direct identification of controller parameters is desired to reduce the design effort and computational load while the IAMBPC involves a two-stage process of model identification and controller design. The former method only requires a single QR decomposition for obtaining the controller parameters and uses a receding horizon approach to process input / output data for the identification. A suboptimal SVD-based optimisation technique is proposed to incorporate the input constraints. The proposed techniques are implemented and tested on a fourth order non- linear model of a wastewater system. Simulation results are presented to compare the direct and indirect adaptive methods and to demonstrate the performance of the proposed algorithms The Institution of Engineering and Technology 2011 Article PeerReviewed Abd. Wahab, Norhaliza and Katebi, R. and Balderud, J. and Rahmat, M. F. (2011) Data-driven adaptive model-based predictive control with application in wastewater systems. IET Control Theory and Applications, 5 (6). pp. 803-812. ISSN 1751-8644 DOI:10.1049/iet-cta.2010.006
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TD Environmental technology. Sanitary engineering
spellingShingle TD Environmental technology. Sanitary engineering
Abd. Wahab, Norhaliza
Katebi, R.
Balderud, J.
Rahmat, M. F.
Data-driven adaptive model-based predictive control with application in wastewater systems
description This study is concerned with the development of a new data-driven adaptive model-based predictive controller (MBPC) with input constraints. The proposed methods employ subspace identification technique and a singular value decomposition (SVD)-based optimisation strategy to formulate the control algorithm and incorporate the input constraints. Both direct adaptive model-based predictive controller (DAMBPC) and indirect adaptive model-based predictive controller (IAMBPC) are considered. In DAMBPC, the direct identification of controller parameters is desired to reduce the design effort and computational load while the IAMBPC involves a two-stage process of model identification and controller design. The former method only requires a single QR decomposition for obtaining the controller parameters and uses a receding horizon approach to process input / output data for the identification. A suboptimal SVD-based optimisation technique is proposed to incorporate the input constraints. The proposed techniques are implemented and tested on a fourth order non- linear model of a wastewater system. Simulation results are presented to compare the direct and indirect adaptive methods and to demonstrate the performance of the proposed algorithms
format Article
author Abd. Wahab, Norhaliza
Katebi, R.
Balderud, J.
Rahmat, M. F.
author_facet Abd. Wahab, Norhaliza
Katebi, R.
Balderud, J.
Rahmat, M. F.
author_sort Abd. Wahab, Norhaliza
title Data-driven adaptive model-based predictive control with application in wastewater systems
title_short Data-driven adaptive model-based predictive control with application in wastewater systems
title_full Data-driven adaptive model-based predictive control with application in wastewater systems
title_fullStr Data-driven adaptive model-based predictive control with application in wastewater systems
title_full_unstemmed Data-driven adaptive model-based predictive control with application in wastewater systems
title_sort data-driven adaptive model-based predictive control with application in wastewater systems
publisher The Institution of Engineering and Technology
publishDate 2011
url http://eprints.utm.my/id/eprint/44832/
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score 13.250246