Accelerated Direct-Problem Solution: A Complementary Method for Computational Time Reduction

Alberto Prieto-Moreno (), Leôncio D. Tavares Câmara () and Orestes Llanes-Santiago ()
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Alberto Prieto-Moreno: Instituto Superior Politécnico José Antonio Echeverri̧a (CUJAE), Automatic and Computing Department
Leôncio D. Tavares Câmara: Polytechnic Institute, IPRJ-UERJ, Mechanical Engineering and Energy Department
Orestes Llanes-Santiago: Instituto Superior Politécnico José Antonio Echeverri̧a (CUJAE), Automatic and Computing Department

Chapter Chapter 8 in Mathematical Modeling and Computational Intelligence in Engineering Applications, 2016, pp 105-120 from Springer

Abstract: Abstract This paper presents a proposal designed to reduce the time required by the process to estimate the parameters of a system by accelerating the direct-problem solution as the slow phase in any estimation method. This proposal is considered a complement to existing procedures, such as the combination of different optimization methods for the purpose of reducing the number of calls to the objective function. The proposal consists of a procedure that helps study the relation between the direct-problem solution step and the time required for this solution, as well as the influence of the direct solution’s built-in error on the accuracy of the estimated parameters. Consequently, the extent in which the estimation process can be accelerated without impairing estimation accuracy can be determined. For the purpose of testing its viability, this proposal was applied to the estimation problem of the kinetic parameters of a chromatography column process, as modeled using the front-velocity method. The results from this test show that, by accelerating the direct-problem solution, the estimation time can be reduced significantly, without affecting the accuracy of the estimation.

Keywords: Parameter estimation; Accuracy; Computational cost; Direct solution; Chromatographic column; Front velocity; Kinetic parameters (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-38869-4_8

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DOI: 10.1007/978-3-319-38869-4_8

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