An application of the brain limbic system–based control to the electromechanical brake system

Changwon Kim; Yeesock Kim; Ohwon Kwon; Joonho Seo; Dongkyu Lee; Hak Yi

doi:10.1177/1687814018755215

An application of the brain limbic system–based control to the electromechanical brake system

Changwon Kim, Yeesock Kim, Ohwon Kwon, Joonho Seo, Dongkyu Lee, Hak Yi

Research output: Contribution to journal › Article › peer-review

13 Scopus citations

Abstract

Recently, many mechanical components of vehicles are being replaced by electrical or electromechanical parts. This change leads to the reduced weight, higher fuel efficiency, and simpler diagnosis. In particular, a reliable and robust electromechanical brake control system has been focused. So, this article investigates that an application of brain limbic system–based control, a bio-inspired control strategy, to an electromechanical brake system is suitable for dynamic and uncertain driving conditions. To do this end, control parameters are optimized through genetic algorithm. Results show the effectiveness of the suggested control method in terms of control speed, reference tracking, and robustness to the disturbance.

Original language	English
Journal	Advances in Mechanical Engineering
Volume	10
Issue number	2
DOIs	https://doi.org/10.1177/1687814018755215
State	Published - 1 Feb 2018

Keywords

Brain limbic system–based control
electromechanical braking
genetic algorithm

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10.1177/1687814018755215

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title = "An application of the brain limbic system–based control to the electromechanical brake system",

abstract = "Recently, many mechanical components of vehicles are being replaced by electrical or electromechanical parts. This change leads to the reduced weight, higher fuel efficiency, and simpler diagnosis. In particular, a reliable and robust electromechanical brake control system has been focused. So, this article investigates that an application of brain limbic system–based control, a bio-inspired control strategy, to an electromechanical brake system is suitable for dynamic and uncertain driving conditions. To do this end, control parameters are optimized through genetic algorithm. Results show the effectiveness of the suggested control method in terms of control speed, reference tracking, and robustness to the disturbance.",

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AU - Kim, Yeesock

AU - Kwon, Ohwon

AU - Seo, Joonho

AU - Lee, Dongkyu

AU - Yi, Hak

PY - 2018/2/1

Y1 - 2018/2/1

N2 - Recently, many mechanical components of vehicles are being replaced by electrical or electromechanical parts. This change leads to the reduced weight, higher fuel efficiency, and simpler diagnosis. In particular, a reliable and robust electromechanical brake control system has been focused. So, this article investigates that an application of brain limbic system–based control, a bio-inspired control strategy, to an electromechanical brake system is suitable for dynamic and uncertain driving conditions. To do this end, control parameters are optimized through genetic algorithm. Results show the effectiveness of the suggested control method in terms of control speed, reference tracking, and robustness to the disturbance.

AB - Recently, many mechanical components of vehicles are being replaced by electrical or electromechanical parts. This change leads to the reduced weight, higher fuel efficiency, and simpler diagnosis. In particular, a reliable and robust electromechanical brake control system has been focused. So, this article investigates that an application of brain limbic system–based control, a bio-inspired control strategy, to an electromechanical brake system is suitable for dynamic and uncertain driving conditions. To do this end, control parameters are optimized through genetic algorithm. Results show the effectiveness of the suggested control method in terms of control speed, reference tracking, and robustness to the disturbance.

KW - Brain limbic system–based control

KW - electromechanical braking

KW - genetic algorithm

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An application of the brain limbic system–based control to the electromechanical brake system

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Keywords

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