Model Predictive Path-Following Control of an AR . Drone Quadrotor

Andres Hernandez, Harold Murcia, Cosmin Copot, Robin De Keyser

Resultado de la investigación: Contribución a una revistaArtículo

Resumen

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.
Idioma originalInglés estadounidense
Páginas (desde-hasta)618-623
Número de páginas6
PublicaciónMemorias del XVI Congreso Latinoamericano de Control Automático
Volumen48
N.º3
EstadoPublicada - 2014

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