Multiply-connected neuro PID control of ultra-compact binary power plant

Kun Young Han, HeeHyol Lee

Research output: Contribution to journalArticle

Abstract

An ultra-compact binary power plant converts thermal energy into electric power using low temperature difference thermal energy between heat source and cooling source. In control of the binary power plant, the negative effects such as characteristic changes caused by environmental condition and corrosion of related equipment, and coupling between control loops are the main difficulties in designing a controller and fine-tuning its parameters. In order to realize the stable power generation it is necessary to consider a control system to keep control performance when characteristic change of the binary power plant, and to compensate coupling in Multi-Input and Multi-Output (MIMO) systems. A Multiply-Connected (MC) Neuro PID control system using a Neural Network architecture connected directly by neurons of each control loop is proposed to overcome above difficulties, and its strategy for design of the control system is introduced. The proposed MC Neuro PID control system is compared to traditional control systems to show the effectiveness of the MC Neuro PID control through simulations in this paper.

Original languageEnglish
Pages (from-to)504-513
Number of pages10
JournalIEEJ Transactions on Electronics, Information and Systems
Volume139
Issue number4
DOIs
Publication statusPublished - 2019 Jan 1

Fingerprint

Three term control systems
Power plants
Control systems
Thermal energy
Network architecture
Neurons
Power generation
Tuning
Corrosion
Cooling
Neural networks
Controllers
Temperature

Keywords

  • Binary power plant
  • Low-temperature difference thermal energy
  • Multiply-Connected Neuro PID

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Multiply-connected neuro PID control of ultra-compact binary power plant. / Han, Kun Young; Lee, HeeHyol.

In: IEEJ Transactions on Electronics, Information and Systems, Vol. 139, No. 4, 01.01.2019, p. 504-513.

Research output: Contribution to journalArticle

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