Controller and Trajectory Optimization for a Quadrotor UAV with Parametric Uncertainty

被引:3
|
作者
Srour, Ali [1 ]
Franchi, Antonio [2 ,3 ,4 ]
Giordano, Paolo Robuffo [1 ]
机构
[1] Univ Rennes, CNRS, INRIA, IRISA, Campus Beaulieu, Rennes, France
[2] Univ Twente, Elect Engn Math Comp Sci EEMCS Fac, Robot & Mech Dept, NL-7500 AE Enschede, Netherlands
[3] Sapienza Univ Rome, Dept Comp Control & Management Engn, I-00185 Rome, Italy
[4] Univ Toulouse, CNRS, LAAS, F-31000 Toulouse, France
来源
2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) | 2023年
基金
欧盟地平线“2020”;
关键词
D O I
10.1109/IROS55552.2023.10341739
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this work, we exploit the recent notion of closed-loop state sensitivity to critically compare three typical controllers for a quadrotor UAV with the goal of evaluating the impact of controller choice, gain tuning and shape of the reference trajectory in minimizing the sensitivity of the closed-loop system against uncertainties in the model parameters. To this end, we propose a novel optimization problem that takes into account both the shape of the reference trajectory and the controller gains. We then run a large statistical campaign for comparing the performance of the three controllers which provides some interesting insight for the goal of increasing closed-loop robustness against parametric uncertainties.
引用
收藏
页码:9999 / 10005
页数:7
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