Neuro PID control of power generation using a low temperature gap

Kun Young Han, Hee Hyol Lee

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Power generation using a low temperature gap converts heat energy into electricity by using the temperature difference. In this article, a simulation model for power generation using a low temperature gap, which uses a circulation cycle with ammonia as the working fluid, is constructed as a linear multiple input/multiple output (MIMO) model which has 2 inputs and 2 outputs based on the step response method. A PID controller using a back propagation neural network is designed so that the difference in pressure between the turbine inlet and outlet is kept at 0.3 Mpa.

Original languageEnglish
Pages (from-to)178-184
Number of pages7
JournalArtificial Life and Robotics
Volume16
Issue number2
DOIs
Publication statusPublished - 2011 Sep 1

Keywords

  • Evaporator
  • Neural network
  • PID control
  • Power generation
  • Turbine

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence

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