Branch and bound method for multiobjective pairing selection
Most of the available methods for selection of input-output pairings for decentralized control require evaluation of all alternatives to find the optimal pairings. As the number of alternatives grows rapidly with process dimensions, pairing selection through an exhaustive search can be computationa...
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sg-ntu-dr.10356-914682023-12-29T06:48:11Z Branch and bound method for multiobjective pairing selection Kariwala, Vinay Cao, Yi School of Chemical and Biomedical Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering Most of the available methods for selection of input-output pairings for decentralized control require evaluation of all alternatives to find the optimal pairings. As the number of alternatives grows rapidly with process dimensions, pairing selection through an exhaustive search can be computationally forbidding for large-scale processes. Furthermore, the different criteria can be conflicting necessitating pairing selection in a multiobjective optimization framework. In this paper, an efficient branch and bound (BAB) method for multiobjective pairing selection is proposed. The proposed BAB method is illustrated through a biobjective pairing problem using selection criteria involving the relative gain array and the µ-interaction measure. The computational efficiency of the proposed method is demonstrated by using randomly generated matrices and the large-scale case study of cross-direction control. Accepted version 2010-12-17T02:58:33Z 2019-12-06T18:06:13Z 2010-12-17T02:58:33Z 2019-12-06T18:06:13Z 2010 2010 Journal Article Kariwala, V., & Cao, Y. (2010). Branch and bound method for multiobjective pairing selection. Automatica, 46(5), 932-936. 0005-1098 0005-1098 https://hdl.handle.net/10356/91468 http://hdl.handle.net/10220/6492 150894 en Automatica 6 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering Kariwala, Vinay Cao, Yi Branch and bound method for multiobjective pairing selection |
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Most of the available methods for selection of input-output pairings for decentralized control require evaluation of all alternatives to find the optimal pairings. As the number of alternatives grows rapidly with process dimensions, pairing selection through an exhaustive search can be computationally forbidding for large-scale processes. Furthermore, the different criteria can be conflicting necessitating pairing selection in a multiobjective optimization framework. In this paper, an efficient branch and bound (BAB) method for multiobjective pairing selection is proposed. The proposed BAB method is illustrated through a biobjective pairing problem using selection criteria involving the relative gain array and the µ-interaction measure. The computational efficiency of the proposed method is demonstrated by using randomly generated matrices and the large-scale case study of cross-direction control. |
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School of Chemical and Biomedical Engineering |
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School of Chemical and Biomedical Engineering Kariwala, Vinay Cao, Yi |
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Article |
author |
Kariwala, Vinay Cao, Yi |
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Kariwala, Vinay |
title |
Branch and bound method for multiobjective pairing selection |
title_short |
Branch and bound method for multiobjective pairing selection |
title_full |
Branch and bound method for multiobjective pairing selection |
title_fullStr |
Branch and bound method for multiobjective pairing selection |
title_full_unstemmed |
Branch and bound method for multiobjective pairing selection |
title_sort |
branch and bound method for multiobjective pairing selection |
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2010 |
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https://hdl.handle.net/10356/91468 http://hdl.handle.net/10220/6492 |
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1787136572677685248 |