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Processes 2017, 5(1), 1; doi:10.3390/pr5010001

An Analysis of the Directional-Modifier Adaptation Algorithm Based on Optimal Experimental Design

Department of Signals and Systems, Chalmers University of Technology, SE-412 96 Göteborg, Sweden
Academic Editor: Dominique Bonvin
Received: 1 November 2016 / Revised: 28 November 2016 / Accepted: 15 December 2016 / Published: 22 December 2016
(This article belongs to the Special Issue Real-Time Optimization)
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Abstract

The modifier approach has been extensively explored and offers a theoretically-sound and practically-useful method to deploy real-time optimization. The recent directional-modifier adaptation algorithm offers a heuristic to tackle the modifier approach. The directional-modifier adaptation algorithm, supported by strong theoretical properties and the ease of deployment in practice, proposes a meaningful compromise between process optimality and quickly improving the quality of the estimation of the gradient of the process cost function. This paper proposes a novel view of the directional-modifier adaptation algorithm, as an approximation of the optimal trade-off between the underlying experimental design problem and the process optimization problem. It moreover suggests a minor modification in the tuning of the algorithm, so as to make it a more genuine approximation. View Full-Text
Keywords: modifier approach; directional-modifier adaptation; experimental design; optimality loss function modifier approach; directional-modifier adaptation; experimental design; optimality loss function
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Gros, S. An Analysis of the Directional-Modifier Adaptation Algorithm Based on Optimal Experimental Design. Processes 2017, 5, 1.

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