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http://dx.doi.org/10.6109/jkiice.2021.25.11.1495

Neuro PID Control for Ultra-Compact Binary Power Generation Plant  

Han, Kun-Young (AI Grand ICT Research Center, Dong-Eui University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.25, no.11, 2021 , pp. 1495-1504 More about this Journal
Abstract
An ultra-compact binary power generation plant converts thermal energy into electric power using temperature difference between heat source and cooling source. In the actual power generation environment, the characteristic value of the plant changes due to any negative effects such as environmental condition or corrosion of related equipment. If the characteristic value of the plant changes, it may lead to unstable output of the turbine in a conventional PID control system with fixed PID parameters. A Neuro PID control system based on Neural Network adaptively to adjust the PID parameters according to the change in the characteristic value of the plant is proposed in this paper. Discrete-time transfer function models to represent the dynamic characteristics near the operating point of the investigated plant are deduced, and a design strategy of the proposed control system is described. The proposed Neuro PID control system is compared with the conventional PID control system, and its effectiveness is demonstrated through the simulation results.
Keywords
Low-temperature difference thermal energy; Binary power plant; Neural Network; PID control;
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