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Artificial Neural Networks for System Identification and Control

Autor Serhat Seker, Tahir Cetin Akinci, Alfredo A. Martinez-Morales
en Limba Engleză Hardback – 30 apr 2026
In an age where intelligent systems are transforming engineering practice, Artificial Neural Networks for System Identification and Control offers a clear roadmap to mastering artificial intelligence (AI)‑driven modeling and control. From mathematical neuron models to adaptive Artificial Neural Network (ANN)‑based controllers, this book combines theory, algorithms, and hands‑on coding to help readers design and analyze intelligent systems. Rich with visual examples and real‑world case studies, it demonstrates how neural networks outperform traditional control methods in handling nonlinearity, uncertainty, and dynamic system behavior.
  • Offers a practical and accessible guide to ANN‑based system identification and control
  • Blends mathematical insight with real engineering applications
  • Provides Python‑supported examples and visual case studies
  • Highlights key advances in nonlinear modeling and adaptive control design
  • Bridges the gap between theory, simulation, and real‑world deployment
This book is intended for engineers, researchers, and advanced students seeking to apply artificial intelligence to control theory, robotics, and signal processing and to design smarter, more adaptive engineering systems.
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Specificații

ISBN-13: 9781041049111
ISBN-10: 1041049110
Pagini: 114
Ilustrații: 180
Dimensiuni: 156 x 234 mm
Ediția:1
Editura: CRC Press
Colecția CRC Press

Public țintă

General

Cuprins

1. Introduction. 2. Artificial Neuron and Its Mathematical Model. 3. Information Flow or Information Content of NN Structure. 4. Backpropagation Algorithm. 5. Dynamical Neural Networks. 6. System Identification and Use of Neural Networks. 7. Neural Network for Applications of Control Theory. 8. Condition Monitoring with Neural Nets.

Notă biografică

Serhat Seker currently serves as a Full Professor in the Department of Electrical Engineering at Istanbul Technical University (ITU). He completed his undergraduate studies in electrical engineering and pursued his graduate education in electrical and nuclear engineering. His academic and research interests focus on cognitive systems, data processing, signal analysis, and the artificial intelligence–based monitoring of energy systems. Professor Seker has extensive international research experience, having collaborated with research groups at the University of Tennessee in the United States and the Energy Research Centre of the Netherlands. In recognition of his scientific contributions, he was awarded the title of Honorary Professor by the National University of Radio Electronics in Ukraine. Between 2014 and 2020, he served as the Dean of the Faculty of Electrical and Electronics Engineering at ITU, where he played a significant role in academic and administrative development. He currently teaches in the Department of Electrical Engineering at ITU and at ESIGELEC Graduate School of Engineering in France. In addition, he provides academic consultancy for the establishment and development of the Electrical Engineering Department at the University of Djibouti in Africa, where he also teaches. Alongside his scientific research, Professor Seker is an active author, having published ten books, including one textbook, as well as numerous articles, conference papers, and seminar contributions.
Tahir Cetin Akinci (Senior Member, IEEE) earned a bachelor’s degree in electrical engineering in 2000, followed by a master’s and PhD in 2005 and 2010, respectively. From 2003 to 2010, he served as a Research Assistant in the Department of Electrical Engineering at Marmara University in Istanbul, Türkiye. In 2020, he was promoted to Full Professor at Istanbul Technical University (ITU), where he also held administrative appointments, including Associate Dean of the Graduate School and the Faculty of Electrical and Electronics Engineering. Dr. Akinci is currently engaged in academic and research activities at the University of California, Riverside (UCR), within the Bourns College of Engineering Center for Environmental Research and Technology (CE‑CERT). His research interests include artificial neural networks, deep learning, machine learning, cognitive systems, signal processing, power systems, renewable energy systems, and data analytics. He continues to contribute to both theoretical and applied research in intelligent systems and data‑driven modeling.
Alfredo A. Martinez‑Morales serves as the Managing Director of the Southern California Research Initiative for Solar Energy (SC‑RISE) and holds the position of Research Professor at the Bourns College of Engineering Center for Environmental Research and Technology (CE‑CERT). He earned a BS, an MS, and a PhD in electrical engineering at the University of California, Riverside (UCR) in 2005, 2008, and 2010, respectively. His current research focuses on solar cells, alkali metal ion batteries, highly integrated renewables, energy storage systems, and microgrids. Dr. Martinez‑Morales plays a key role as a principal investigator in the Sustainable Integrated Grid Initiative and the Distributed Energy Resources Laboratory at UCR, contributing to the engineering, permitting, and deployment of microgrids throughout Southern California.

Descriere

In an age where intelligent systems are transforming engineering practice, Artificial Neural Networks for System Identification & Control offers a clear roadmap to mastering AI-driven modeling and control.