This book gathers applied artificial intelligence and machine learning methods that supply exactly that layer, across autonomous vehicles, renewable-energy operations, and the condition monitoring of rotating machinery. Mechatronic systems increasingly depend on a layer of intelligence that turns sensor measurements into decisions and actions. It shows how learning-based models, from neural networks and ensemble regressors to reinforcement learning agents, are used to perceive, predict, and act within real mechatronic and energy systems.

Dr. Aydin Azizi holds a Ph.D. in mechanical engineering–mechatronics, a M.Sc. in mechatronics, and a B.Sc. in mechanical engineering. He is a as Fellow of the Higher Education Academy, Official Instructor for the Siemens Mechatronic Certification Program (SMSCP), and Editor-in-Chief of the book series Emerging Trends in Mechatronics published by Springer Nature Group. He currently serves as Senior Lecturer and Academic Partnership Liaison Manager at Oxford Brookes University. His current research focuses on investigating and developing novel techniques to model, control, and optimize complex systems, with expertise in control and automation, AI, and simulation techniques.