Model Predictive Path-Following Control of an AR.Drone Quadrotor
نویسندگان
چکیده
This paper addresses the design and implementation of the Extended Prediction Self-Adaptive Control (EPSAC) approach to Model Predictive Control (MPC) for path-following. Special attention is paid to the closed-loop performance in order to achieve a fast response without overshoot, which are the necessary conditions to ensure the desired tracking performance in confined or indoor environments. The performance of the proposed MPC strategy is compared to the one achieved using PD controllers. Experimental results using the low-cost quadrotor AR.Drone 2.0 validate the reliability of the proposed strategy for 2D and 3D movements.
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