Estimating Real Process Derivatives in on-Line Optimization - A Review

M. Mansour

2012

Abstract

The solution of the Integrated System Optimization and Parameter Estimation (ISOPE) problem necessitates the calculus of real process output derivatives with respect to the inputs. This information is needed in order to satisfy first and second order optimality conditions. Several methods exist and have been developed for calculating these derivatives. In this paper a review of most of the existing methods is presented, in which the Finite Difference Approximation, Dual Control Optimization, Broydon’s method, Dynamic Model Identification, with both linear and nonlinear models, together with a neural networks scheme are presented and applied, under simulation, to a cascade Continuous Stirred Tank Reactor (CSTR) system. The results are then discussed and compared to identify the advantages and disadvantages of using each method.

References

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Paper Citation


in Harvard Style

Mansour M. (2012). Estimating Real Process Derivatives in on-Line Optimization - A Review . In Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-8565-20-4, pages 120-124. DOI: 10.5220/0004059101200124


in Bibtex Style

@conference{simultech12,
author={M. Mansour},
title={Estimating Real Process Derivatives in on-Line Optimization - A Review},
booktitle={Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2012},
pages={120-124},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004059101200124},
isbn={978-989-8565-20-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Estimating Real Process Derivatives in on-Line Optimization - A Review
SN - 978-989-8565-20-4
AU - Mansour M.
PY - 2012
SP - 120
EP - 124
DO - 10.5220/0004059101200124