A learning control of unused energy power generation

Satomi Shikasho; Kun Young Han; Ji Sun Shin; Chui ChengYou; Hee Hyol Lee

doi:10.1007/s10015-010-0842-3

A learning control of unused energy power generation

Satomi Shikasho, Kun Young Han^*, Ji Sun Shin, Chui ChengYou, Hee Hyol Lee

^*Corresponding author for this work

Graduate School of Information, Production and Systems

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

1 Citation (Scopus)

Abstract

In recent years, the development of new clean energy without dependence on fossil fuel has become urgent. This article proposes a learning control system for power generation using a low-temperature gap which has been designed to maintain the speed of a steam turbine in a real environment. This system includes nonlinearity and the characteristics of changing parameters with age and deterioration, as in the real environment. The evaporator, condenser, and turbine systems have been modeled, and a PID control with the ability to learn, based on a BackPropagation neural network, has been designed.

Original language	English
Pages (from-to)	450-454
Number of pages	5
Journal	Artificial Life and Robotics
Volume	15
Issue number	4
DOIs	https://doi.org/10.1007/s10015-010-0842-3
Publication status	Published - 2010 Dec 1

Keywords

BP neural network
Evaporator
Learning control
Low thermal gap
Power generator
Turbine

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology(all)
Artificial Intelligence

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10.1007/s10015-010-0842-3

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title = "A learning control of unused energy power generation",

abstract = "In recent years, the development of new clean energy without dependence on fossil fuel has become urgent. This article proposes a learning control system for power generation using a low-temperature gap which has been designed to maintain the speed of a steam turbine in a real environment. This system includes nonlinearity and the characteristics of changing parameters with age and deterioration, as in the real environment. The evaporator, condenser, and turbine systems have been modeled, and a PID control with the ability to learn, based on a BackPropagation neural network, has been designed.",

keywords = "BP neural network, Evaporator, Learning control, Low thermal gap, Power generator, Turbine",

author = "Satomi Shikasho and Han, {Kun Young} and Shin, {Ji Sun} and Chui ChengYou and Lee, {Hee Hyol}",

year = "2010",

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TY - JOUR

T1 - A learning control of unused energy power generation

AU - Shikasho, Satomi

AU - Han, Kun Young

AU - Shin, Ji Sun

AU - ChengYou, Chui

AU - Lee, Hee Hyol

PY - 2010/12/1

Y1 - 2010/12/1

N2 - In recent years, the development of new clean energy without dependence on fossil fuel has become urgent. This article proposes a learning control system for power generation using a low-temperature gap which has been designed to maintain the speed of a steam turbine in a real environment. This system includes nonlinearity and the characteristics of changing parameters with age and deterioration, as in the real environment. The evaporator, condenser, and turbine systems have been modeled, and a PID control with the ability to learn, based on a BackPropagation neural network, has been designed.

AB - In recent years, the development of new clean energy without dependence on fossil fuel has become urgent. This article proposes a learning control system for power generation using a low-temperature gap which has been designed to maintain the speed of a steam turbine in a real environment. This system includes nonlinearity and the characteristics of changing parameters with age and deterioration, as in the real environment. The evaporator, condenser, and turbine systems have been modeled, and a PID control with the ability to learn, based on a BackPropagation neural network, has been designed.

KW - BP neural network

KW - Evaporator

KW - Learning control

KW - Low thermal gap

KW - Power generator

KW - Turbine

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JO - Artificial Life and Robotics

JF - Artificial Life and Robotics

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A learning control of unused energy power generation

Abstract

Keywords

ASJC Scopus subject areas

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