Mechatronic Systems

Modelling, Sensing, and Intelligent Control
Erscheinungsjahr 2027
ISBN: 978-981-9254-69-9
Verlag: Springer

Buch, Englisch, 212 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Emerging Trends in Mechatronics

This book brings together the foundational methodology and the emerging research directions that define how modern mechatronic systems are designed, instrumented, modelled, and controlled. It moves from systematic design and multi-domain modelling, through the sensing and actuation hardware that connects a system to its environment, to advanced AI-enhanced estimation for switched and uncertain dynamics, offering a coherent path from established practice to current frontiers.

The contributors approach each topic with both analytical rigour and practical orientation. Mathematical models are derived from first principles and validated against simulation and hardware, sensing and actuation are treated as coupled mechanical, electrical, and control problems rather than catalogue selections, and learning-based methods are integrated in a way that preserves stability guarantees rather than discarding them. The result is a focused reference that supports readers who need to build reliable systems as well as those investigating new methods for estimation and control under uncertainty.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Mobki, Hamed

Azizi, Aydin

Fachgebiete

• Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle

Inhaltsverzeichnis

Design Methodology and Modeling of Mechatronic Systems.- Sensor and Actuator Systems in Mechatronics.- AI Enhanced Observer Design for Switched and Hybrid Systems with Uncertainties.- Stochastic non parametric shock absorber model.

Über Autor(innen)

Dr. Hamed Mobki holds a Ph.D. in Mechanical Engineering, together with two master’s degrees, one in Mechanical Engineering and the other in Electrical Engineering with a specialisation in Control, and a bachelor’s degree in Mechanical Engineering. He previously served as a researcher at GUtech Oman, in collaboration with RWTH Aachen. He currently holds the position of Researcher and Condition Monitoring Specialist at the West Azerbaijan Power Generation Management Company and the Urmia Combined Cycle Power Plant. His research interests encompass a broad spectrum of topics within mechanical and mechatronic engineering, including condition monitoring, vibration and control analysis, and the dynamics of complex systems.

Dr. Aydin Azizi holds a Ph.D. in Mechanical Engineering with a specialisation in Mechatronics, an M.Sc. in Mechatronics, and a BSc in Mechanical Engineering. He is a fellow of the Higher Education Academy, an official instructor for the Siemens Mechatronic Systems Certification Program (SMSCP), and an editor-in-chief of the Emerging Trends in Mechatronics book series published by Springer Nature. He currently serves as a senior lecturer and the Academic Partnership Liaison Manager at Oxford Brookes University. His current research focuses on investigating and developing novel techniques to model, control, and optimise complex systems, with expertise in control and automation, artificial intelligence, and simulation techniques.