Adaptive control for an unmanned aerial vehicle under payload variation with precision agriculture applications
Abstract
This paper presents a model reference adaptive control for a quadrotor under payload variations, in this way, drone's mass and moments of inertia are considered uncertain parameters in its dynamics. The control design considers the analysis of the underactuated model of the drone dynamics, which can be decomposed into three independent subsystems. For each subsystem a reference model is proposed and using the Lyapunov formalism, a feedback control law is obtained in order to stabilize the vehicle together with an adaptation rule that adjusts the uncertain parameters online. This results in a backstepping control scheme with adaptive capabilities. The stability analysis also guarantees the convergence of the states of each subsystem to those of its corresponding reference model. To evaluate the performance of the proposed controller, numerical simulations were developed in MATLAB Simulink.
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References
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