Nonlinear Control of Robots and Unmanned Aerial Vehicles

Nonlinear Control of Robots and Unmanned Aerial Vehicles: An Integrated Approach focuses on the design of nonlinear, automatic, and autonomous controllers for robots including drones and unmanned aerial vehicles. It presents the control and regulation methods that rely on the 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 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.

Ranjan Vepa is currently a Reader in Aerospace Engineering in the School of Engineering and Material Science, Queen Mary University of London, UK. He obtained his Ph. D. in Applied Mechanics in 1975 from Stanford University, USA. His research interests include design of control systems and associated signal processing with applications in aerospace systems, smart structures, space-robotics, energy, and biomedical systems. Dr. Vepa teaches Master's level courses on Advanced Spacecraft Design, Aircraft Flight Control and Simulation, Aeroelasticity and Robotics. He is also a Member of the Royal Aeronautical Society, London and a Fellow of the UK's Higher Education Academy. Dr. Vepa is the author of eight books including Electric Aircraft Dynamics: A Systems Engineering Approach (CRC Press, 2020) and Flight Dynamics, Simulation, and Control: For Rigid and Flexible Aircraft (Second Edition, CRC Press, 2023).

1. Lagrangian methods and robot dynamics. 2. Unmanned aerial vehicle dynamics and Lagrangian methods. 3. Feedback linearization. 4. Linear and phase plane analysis of stability. 5. Robot and UAV control. 6. Stability. 7. Lyapunov stability. 8. Computed torque control. 9. Sliding mode control. 10. Parameter identification. 11. Adaptive and model predictive control. 12. Lyapunov design: The backstepping approach. 13. Hybrid position and force control. 14. Autonomous Control of UAVs and Robots.