Backstepping Control for a Quadrotor Helicopter
By T. Madani, Abdelaziz Benallegue. 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006
617 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/c371dd41084f0aab7627e7950cf5e0be411c3e29
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Timothy W. McLain
- R. Beard
- Robert C. Leishman
- Frank L. Lewis
- John Macdonald
- Kamesh Subbarao
- Aníbal Ollero
- Abhijit Das
In Control and Systems Engineering
- R. Beard
- Frank L. Lewis
- Timothy W. McLain
- John Macdonald
- Kamesh Subbarao
- Aníbal Ollero
- Abhijit Das
- Robert C. Leishman
Citations in the corpus
- Reinforcement Learning for UAV Attitude Control (2018, neutral): “Additionally numerous other nonlinear control algorithms have been developed and applied to flight control, including feedback linearization [25], sliding mode control [25], and backstepping [28], in an attempt to model the nonlinear dynamics of the aircraft.”
- Quadrotors and Accelerometers: State Estimation with an Improved Dynamic Model (2014, background): “Other approaches include a drag force that is directly proportional to the quadrotor’s linear velocity [13]–[16].”
- Aerodynamics and Control of Quadrotors (2017, background): “Their simple design with simple dynamics have made them the preferred platform for aerial robotics research as well as the amateur and hobby community Mahony et al. [2012]; Lim et al.”
- Backstepping Approach for Controlling a Quadrotor Using Lagrange Form Dynamics (2009, background): “The dynamics of a quadrotor [3–7] are a simplified form of helicopter dynamics that exhibit the basic problems of rotorcraft including underactuation, strong coupling, multi-input/multi-output design, and unknown nonlinearities.”
- Aerial Manipulation: A Literature Review (2018, methodology): “approaches rely upon backstepping [17], impedance [18] and optical flow [19] techniques.”
- A survey of quadrotor Unmanned Aerial Vehicles (2012, background): “Various control structures ranging from basic PID controllers [15, 27, 62] to more complex systems using backstepping or neural networks [16, 26, 46] have proved to be efficient.”