Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes
Two novel hierarchical structures are presented which extend the applicability of previous model based double iterative loop techniques to non-convex problems. The methods incorporate integrated system optimisation and parameter estimation which utilizes process measurements to achieve real proce...
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| Main Authors: | , , |
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| Format: | Article |
| Published: |
1993
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| Online Access: | http://journalarticle.ukm.my/1309/ http://www.ukm.my/jkukm/index.php/jkukm |
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| Institution: | Universiti Kebangsaan Malaysia |
| Summary: | Two novel hierarchical structures are presented which extend the applicability of
previous model based double iterative loop techniques to non-convex problems. The
methods incorporate integrated system optimisation and parameter estimation which
utilizes process measurements to achieve real process optimality inspite of model
reality differences. The double iterative loop structures of the proposed algorithms
use the real process measurement within the outer loops while the inner loops involve
model based computation only. This means that the algorithms use available
information from the real process efficiently and a significant reduction in set-point
alterations to real subprocesses is achieved. In order to cater for process complexity
the inner loops are organised in the form of two level hierarchical structures. The
paper presents the convergence conditions of the augmented techniques and
simulation examples are provided to illustrate and compare the methods |
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