References
- IEA, World Energy Outlook, 2018.
- Ministry of Land, Infrastructure, and Transport, The Korean New Deal [Internet]. Available: http://www.molit.go.kr/newdeal.
- Y. S. Lee and G. I. Lee, "Thermal energy network concept and research status," Journal of the KSME, vol. 56, no. 8, pp. 32-36, Aug. 2016.
- J. Y. Ki, J. I. Lee, M. S. Kim, and H. S. Han, "Power Generation Technology using waste heat of Industry," Korea Evaluation Institute of Industrial Technology, PD Issue Report, 2017.
- Korea Heating Air-conditioning Refrigeration & renewable energy News (Kharn). Carry forward R&D using unused thermal energy [Internet]. Available: http://www.kharn.kr/news/article.html?no=4709.
- H. Jung, "Organic Rankine(ORC) power generation system using low&medium-grade temperature waste heat," The proceedings of KIEE, vol. 65, no. 5, pp. 34-40, May. 2016.
- D. W. Lee, Technology Market Prospect of Eco-friendly Organic Rankine Cycle Power Generation System, Korea Institute of Science and Technology Information, 2016.
- M. Morita, "Scaling Problem at Binary Cycle Power Plant by Geothermal Water and Development of Material for Inhibiting Scaling," The Japan Institute of Metals and Materials, vol. 57, no. 10, pp. 493-497, 2018.
- Y. G. Song, G. J. Cho, S. H. Kim, Y. I. Kim, H. J. Moon, D. S. Cho, and G. H. Lee, "Development of Waste Heat Recovery Power Generation System Using Scroll Expander," HNC Co., Ltd: Report, 2017.
- KOBELCO. Binary Power Generation System Micro binary [Internet]. Available : https://www.kobelco.co.jp/products/standard_compressors/microbinary/applications.html.
- IHI, Binary Power Generation System Heat Recovery [Internet]. Available: https://www.ihi.co.jp/compressor/binary/product/product.html.
- K. Funahashi, "On the Approximate Realization of identity Mapping by Three-Layer Neural Networks," Electronics and Communications in Japan, vol. 73, no. 11, pp. 61-68, Jan. 1990. https://doi.org/10.1002/ecjc.4430731107
- T. Yabuta and T. Yamada, "Neural Network Controller Characteristics with Regard to Adaptive Control," IEEE Transaction on Systems, Man, and Cybernetics, vol. 22, no. 1, pp. 170-177, Jan/Feb, 1992. https://doi.org/10.1109/21.141322
- D. E. Rumelhart and J. L. McClelland, PDP Research Group, Parallel distributed Processing, Volume1, A Bradford Book, 1989.
- K. Ichikawa, K. Kanai, T. Suzuki, and S. Tamura, Adaptive Control, Japan: Shokodo, 1984.
- B. Karg and S. Lucia, "Stability and feasibility of neural network-based controllers via output range analysis," in Proceeding of the 59th IEEE Conference on Decision and Control(CDC), pp. 4947-4954, Dec, 2020.
- S. Omatsu and T. Yamamoto, Self-tuning control, Japan: The Society of Instrument and Control Engineers, 1996.
- K. S. Narendra and K. Parthetsarathy, "Identification and Control of Dynamic Systems Using Neural Networks," IEEE Transactions on Neural Networks, vol. 1, no. 1, pp. 4-27, Mar. 1990. https://doi.org/10.1109/72.80202
- D. Psaltis, A. Sider, and A. Yamamura, "A Multilayered Neural Network Controller," IEEE Control Systems Magazine, vol. 8, no. 2, pp. 17-22, Apr. 1988. https://doi.org/10.1109/37.1868
- M. I. Jordan, "Generic Constraints on Underspecified Target Trajectories," Proceedings of International Joint Conference on Neural Networks, Washington D.C., pp. 217-225, Aug. 2002.
- M. Kawato, Y. Uno, M. Isobe, and R. Suzuki, "Hierarchical Neural Network Model for Voluntary Movement With Application to Robot," IEEE Control Systems Magazine, vol. 8, no. 2, pp. 8-15, Apr. 1988. https://doi.org/10.1109/37.1867
- F. Xu, D. Tang, and S. Wang, "Research on parallel nonlinear control system of PD and RBF neural network based on U model," Journal for Control, Measurement, Electronics, Computing and Communications, vol. 61, no. 2, pp. 284-294, Mar. 2020.
- S. A. Elbelady, H. E. Fawaz, and A. M. Abdul Aziz, "Online Self Tuning PID Control Using Neural Network for Tracking Control of a pneumatic Cylinder Using Pulse Width Modulation Piloted Digital Valves," International Journal of Mechanical & Mechatronics Engineering, vol. 16, no. 03, pp. 123-136, Jun. 2016.
- K. P. Gama, C. E. Tengum, and W. Hao, "Deep Neural Network Based Self-Tuning PID Control for Quadrotor Attitude," North American Academic Research, vol. 3, no. 11, pp. 465-480, Nov. 2020.
- Y. K. Choi and J. H. Park, "Control Gain Optimization for mobile Robots Using Neural Network and Genetic Algorithms," Journal of the Korea Institute of Information and Communication Engineering, vol. 20, no. 4, pp. 698-706, Apr. 2016. https://doi.org/10.6109/JKIICE.2016.20.4.698
- M. Fouzia, N. Khenfer, and N. E. Boukezzoula, "Robust Adaptive Tracking Control of Manipulator Arms with Fuzzy Neural Networks," Engineering, Technology, Applied Science Research, vol. 10, no. 4, pp. 6131-6141, Aug. 2020. https://doi.org/10.48084/etasr.3648