Mechatronic Systems
Modelling, Sensing, and Intelligent Control
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Beschreibung
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.
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.
Includes worked derivations and case studies, including state-space modelling, Lagrangian and Newton-Euler formulations Presents an AI-enhanced framework for switched and hybrid systems Connects design methodology, sensing and actuation, and intelligent estimation within a single mechatronics framework
Autor*in
Hamed Mobki
Themen in »Mechatronic Systems«
Switched and Hybrid Systems Neural Networks Lagrangian and Newton-Euler derivations V-model life cycle PID design Sensor and Actuator Systems