In this paper we present a robust quadrotor controller for tracking a reference trajectory in presence of uncertainties and disturbances. A Super Twisting controller is implemented using the recently proposed gain adaptation law [1], [2], which has the advantage of not requiring the knowledge of the upper bound of the lumped uncertainties. The controller design is based on the regular form of the quadrotor dynamics, without separation in two nested control loops for position and attitude. The controller is further extended by a feedforward dynamic inversion control that reduces the effort of the sliding mode controller. The higher order quadrotor dynamic model and proposed controller are validated using a SimMechanics physical simulation with initial error, parameter uncertainties, noisy measurements and external perturbations.
Adaptive super twisting controller for a quadrotor UAV / Rajappa, S.; Masone, C.; Bulthoff, H. H.; Stegagno, P.. - 2016:(2016), pp. 2971-2977. (Intervento presentato al convegno 2016 IEEE International Conference on Robotics and Automation, ICRA 2016 tenutosi a Stockholm Waterfront Congress Center (SWE) nel 16-21 May 2016) [10.1109/ICRA.2016.7487462].
Adaptive super twisting controller for a quadrotor UAV
Masone C.;
2016
Abstract
In this paper we present a robust quadrotor controller for tracking a reference trajectory in presence of uncertainties and disturbances. A Super Twisting controller is implemented using the recently proposed gain adaptation law [1], [2], which has the advantage of not requiring the knowledge of the upper bound of the lumped uncertainties. The controller design is based on the regular form of the quadrotor dynamics, without separation in two nested control loops for position and attitude. The controller is further extended by a feedforward dynamic inversion control that reduces the effort of the sliding mode controller. The higher order quadrotor dynamic model and proposed controller are validated using a SimMechanics physical simulation with initial error, parameter uncertainties, noisy measurements and external perturbations.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2975835