Efficient Nonlinear Model Predictive Control for Quadrotor Trajectory Tracking: Algorithms and Experiment

2021 ◽  
pp. 1-12
Author(s):  
Dong Wang ◽  
Quan Pan ◽  
Yang Shi ◽  
Jinwen Hu ◽  
Chunhui Zhao
2021 ◽  
Vol 54 (16) ◽  
pp. 51-56
Author(s):  
Leticia Mayumi Kinjo ◽  
Stefan Wirtensohn ◽  
Johannes Reuter ◽  
Tomas Menard ◽  
Olivier Gehan

2019 ◽  
Vol 42 (2) ◽  
pp. 214-227 ◽  
Author(s):  
Nadia Miladi ◽  
Habib Dimassi ◽  
Salim Hadj Said ◽  
Faouzi M’Sahli

In this paper, we propose an explicit nonlinear model predictive control (ENMPC) method based on a robust observer to solve the trajectory tracking problem for outdoor quadrotors. We take into consideration the external aerodynamic disturbances present in the dynamics of the Newton-Euler quadrotor model. To overcome the effects of these disturbances, a high gain observer combined with a first order sliding mode observer are proposed to estimate both the states and the unknown disturbances using the only positions and angular measurements of the quadrotor. The estimated signals are then used by the predictive controller in order to ensure the trajectory tracking objective. Despite the presence of bounded disturbances, the convergence of the composite controller (ENMPC technique with the latter observers) is guaranteed through a stability analysis. Theoretical results are validated with some numerical simulations showing the good performances of the proposed tracking control approach.


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