Concurrent Learning-Based Inertial Parameter Estimation and Control of Quadrotors
Concurrent Learning-Based Inertial Parameter Estimation and Control of Quadrotors
This research letter proposes an integral concurrent learning (ICL)-based geometric controller for quadrotor UAVs with non-coincident centers of mass. The method estimates mass, CoM offset, and the full inertia matrix online without using accelerometers or numerical derivatives, ensuring trajectory tracking under finite excitation conditions. Effectiveness is validated via simulation.
The authors present a theoretical framework and simulation validation for an integral concurrent learning controller that estimates quadrotor mass, center-of-mass offset, and full inertia matrix online without requiring onboard accelerometers or numerical derivatives.
Source: arXiv Robotics — research abstracts · Read original article ↗
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e estimated parameters converge to their true values under a finite excitation condition. We validate the effectiveness of the proposed algorithm using a simulation example.
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Source：arXiv Robotics — research abstracts · arxiv.org