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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.
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