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Passivity - based control using genetic algorithm for a DC-DC boost power converter

Minh Ngọc Huỳnh 1, 2
Hoài Nghĩa Dương 3, *
Vĩnh Hảo Nguyễn 1
  1. Ho Chi Minh City University of Technology – VNU-HCM, Vietnam
  2. Industrial University of Ho Chi Minh City, Vietnam
  3. Eastern International University, Vietnam
Correspondence to: Hoài Nghĩa Dương, Eastern International University, Vietnam. Email: [email protected].
Volume & Issue: Vol. 6 No. 2 (2023) | Page No.: 1891-1905 | DOI: 10.32508/stdjet.v6i2.1053
Published: 2023-07-28

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Copyright The Author(s) 2018. This article is published with open access by Vietnam National University, Ho Chi Minh city, Vietnam. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0) which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. 

Abstract

In this paper, a passivity – based control of a DC-DC boost power converter using genetic algorithm is proposed. The output of a DC-DC power boost converter is an inductor current. Its input is duty ratio . Using a co-ordinate transformation of state variables and control input, a DC-DC boost power converter is showed to be passive. A new plant is zero-state observable and the equilibrium point at origin of this plant is asymptotically stable. Then, a passivity - based control law is applied to this plant so that a voltage of capacitor x2 is equal to a value of desired voltage Vd when changing control input, duty ratio . The parameters of the passivity – based controller are also adjusted optimally by genetic algorithm using decimal encoder. Simulation results of a passivity – based control are good when the input voltage E, the load resistor R and the desired voltage Vd are varied. With variations of desired voltage Vd, the passivity – based controller supplies small value of IAE (integral absolute error of Vd and x2), small error, and short settling time Finally, simulation results show that the passivity – based control using genetic algorithm is better than the passivity – based control.

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