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Conflict of Interest: In relation to this article, we declare that there is no conflict of interest.

Publication history: Received February 22, 2016
Accepted August 5, 2016

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Extremum seeking control using a partial sum of input-output product

Jietae Lee^† Kwang Soon Lee¹

Department of Chemical Engineering, Kyungpook National University, Daegu 41566, Korea ¹Department of Chemical Biomolecular Engineering, Sogang University, Seoul 04107, Korea

jtlee@knu.ac.kr

Korean Journal of Chemical Engineering, November 2016, 33(11), 3079-3084(6), 10.1007/s11814-016-0223-2

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Abstract

Recent extremum seeking control that uses a continuous perturbation and the integral feedback of perturbation-output product is based on a static nonlinear process. The method can be applied to dynamic nonlinear processes for tracking and maintaining the optimal operating points. It has several tuning parameters, such as the integral controller gain and the magnitude and frequency of the continuous perturbation signal. The frequency of the continuous perturbation signal should be low enough to ensure the time-scale separation between the real-time optimization and the process dynamics for the closed-loop stability. However, for some processes, fast perturbations are preferred because they can be attenuated easily in subsequent processes such as buffers and storages. For this, we propose an extremum seeking control method where the partial sum of perturbation-output product is used for a faster squarewave perturbation. Simulations for two processes of parallel competing reactions have been given, and a simple liquid level system to test extremum seeking control methods is suggested.

Keywords

Extremum Seeking Control Square-wave Perturbation Real-time Optimization Input Multiplicity

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