Adaptive Control of Quadrotor UAVs: A Design Trade Study With Flight Evaluations

By Zachary T. Dydek, Anuradha M. Annaswamy, E. Lavretsky. IEEE Transactions on Control Systems Technology, 2013

562 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/9ee05a9a673d2f493d1f179a239c2f31f5ee06d3

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

1. Daewon Lee
2. Farhad A. Goodarzi
3. Aníbal Ollero
4. Taeyoung Lee
5. Vincenzo Lippiello
6. Fabio Ruggiero

In Control and Systems Engineering

1. Daewon Lee
2. Farhad A. Goodarzi
3. Gang Tao
4. Aníbal Ollero
5. Bin Jiang
6. Taeyoung Lee
7. Bin Xian
8. Xu Zhang

Citations in the corpus

• Nonlinear Robust Adaptive Tracking Control of a Quadrotor UAV Via Immersion and Invariance Methodology (2015, methodology): “To compensate for the parametric uncertainties, the adaptive nonlinear control method is a suitable choice and has been widely utilized [11].”
• Aerial Manipulation: A Literature Review (2018, methodology): “have been employed to counteract such disturbances [20], [21], [22], [23], [24], [25].”
• Geometric Adaptive Tracking Control of a Quadrotor Unmanned Aerial Vehicle on SE(3) for Agile Maneuvers (2014, background): “Although adaptive controllers are very robust for quadrotors trajectory tracking in existence of disturbances and uncertainties, most of the studies are based on linearization [18, 19] or simplification [20, 21].”
• Robust Backstepping Sliding-Mode Control and Observer-Based Fault Estimation for a Quadrotor UAV (2016, background): “In the past few years, researchers have paid attention to control and have proposed different kinds of control methods, such as linear and adaptive PID controls [2], [3], dynamic inversion control [4], feedback linearization control [5], [6], model predictive control [7], backstepping control [8], [”
• Mathematical Modelling and Parameter Identification of Quadrotor (a survey) (2014, methodology): “By neglecting higher order terms, the linear model of the rotation is obtained as [20,21]: τ I η 1 q (18) The simplified quaternion based model of the rotation is obtained by linearizing equation (15) using Taylor’s Theorem [18].”