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Nonlinear Control of Robots and Unmanned Aerial Vehicles An Integrated Approach, 2nd Edition [#1042414]
Nonlinear Control of Robots and Unmanned Aerial Vehicles: An Integrated Approach, 2nd Edition
English | 2026 | ISBN: 1041004257 | 524 pages | True PDF,EPUB | 45.11 MB
Nonlinear Control of Robots and Unmanned Aerial Vehicles: An Integrated Approach, Second Edition focuses on the design of nonlinear, automatic and autonomous controllers for robots including drones and unmanned aerial vehicles. It presents control and regulation methods that rely on techniques related to the methods of feedback linearization.The Second Edition features new content on autonomous control and guidance of robotic systems and UAVs, including the incorporation of machine and reinforcement learning techniques into the design of flight controllers. It discusses the development of a systematic adaptive backstepping design of nonlinear control laws for systems with unknown constant parameters. Numerous practical application examples and exercises are included to facilitate readers' understanding of nonlinear control system design for robotic systems and UAVs.This book is intended for aerospace, electrical and mechanical engineers working with robotic systems and designing unmanned aerial vehicles.
Nonlinear Control of Robots and Unmanned Aerial Vehicles: An Integrated Approach, Second Edition focuses on the design of nonlinear, automatic and autonomous controllers for robots including drones and unmanned aerial vehicles. It presents control and regulation methods that rely on techniques related to the methods of feedback linearization.
Nonlinear Control of Robots and Unmanned Aerial Vehicles: An Integrated Approach
, Second Edition focuses on the design of nonlinear, automatic and autonomous controllers for robots including drones and unmanned aerial vehicles. It presents control and regulation methods that rely on techniques related to the methods of feedback linearization.
The Second Edition features new content on autonomous control and guidance of robotic systems and UAVs, including the incorporation of machine and reinforcement learning techniques into the design of flight controllers. It discusses the development of a systematic adaptive backstepping design of nonlinear control laws for systems with unknown constant parameters. Numerous practical application examples and exercises are included to facilitate readers' understanding of nonlinear control system design for robotic systems and UAVs.
This book is intended for aerospace, electrical and mechanical engineers working with robotic systems and designing unmanned aerial vehicles.
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