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  • Format: ePub

This book provides novel approaches to gas turbine (GT) modeling, simulation, and control using artificial neural networks (ANNs). It outlines important considerations for beginning the GT modeling process, highlights research in white-box and black-box modeling, discusses the structure of ANNs and the ANN-based model-building process, and presents a noteworthy ANN-based methodology for offline system identification of GTs. It also covers the modeling of GT transient behavior and start-up operation, and the design of proportional-integral-derivative (PID) and neural network-based controllers.

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Produktbeschreibung
This book provides novel approaches to gas turbine (GT) modeling, simulation, and control using artificial neural networks (ANNs). It outlines important considerations for beginning the GT modeling process, highlights research in white-box and black-box modeling, discusses the structure of ANNs and the ANN-based model-building process, and presents a noteworthy ANN-based methodology for offline system identification of GTs. It also covers the modeling of GT transient behavior and start-up operation, and the design of proportional-integral-derivative (PID) and neural network-based controllers.

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Autorenporträt
Hamid Asgari received his Ph.D in mechanical engineering from the University of Canterbury, Christchurch, New Zealand in 2014. He obtained his ME in aerospace engineering from Tarbiat Modares University, Tehran, Iran, and his BE in mechanical engineering from Iran University of Science and Technology, Tehran. He has worked more than 15 years in his professional field as a lead mechanical engineer and project coordinator in highly prestigious industrial companies. During his professional experience, he has been a key member of engineering teams in design, research and development, and maintenance planning departments. He has invaluable theoretical and hands-on experience in technical support, design, and maintenance of a variety of mechanical equipment and rotating machinery, such as gas turbines, pumps, and compressors, in large-scale projects in power plants and in the oil and gas industry.

XiaoQi Chen is a professor in the Department of Mechanical Engineering at the University of Canterbury, Christchurch, New Zealand. After obtaining his BE in 1984 from South China University of Technology, Guangzhou, he received the China-UK Technical Co-Operation Award for his MS study in the Department of Materials Technology at Brunel University, London, UK (1985-1986) and his Ph.D study in the Department of Electrical Engineering and Electronics at the University of Liverpool, UK (1986-1989). He has been a senior scientist at the Singapore Institute of Manufacturing Technology (1992-2006) and a recipient of the Singapore National Technology Award (1999). His research interests include mechatronic systems, mobile robotics, assistive devices, and manufacturing automation. He has been elected to Fellow of IPENZ and Fellow of SME.