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- W1546783933 abstract "In this work, we present an application of an adaptive neural network observer for estimating the thrust that is generated by individual rotors of a quadrotor UAV with uncertain actuator dynamics. In most of the previous works aimed at controlling quadrotor UAV, the controller implementation is based on the assumption of a static relationship between the input to the motors and the resulting force generated by the rotor-propeller subsystem. However variations in this relation can result in performance degradation of the closed-loop system. Using a nonlinear observer, the estimated thrust can be used in feedback control of UAV, making the closed-loop system more robust to such variations. We consider a nonlinear model of the quadrotor with unknown actuator dynamics and we use an adaptive neural network observer with adaptation laws, derived using Lyapunov stability analysis, to estimate unknown dynamics. The resulting adaptation laws guarantee that the error between actual and estimated thrust produced by each individual rotor is bounded. Simulation results show the estimated thrust values match the actual thrust values with satisfactory accuracy." @default.
- W1546783933 created "2016-06-24" @default.
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- W1546783933 date "2011-11-01" @default.
- W1546783933 modified "2023-09-26" @default.
- W1546783933 title "Thrust Estimation of Quadrotor UAV using Adaptive Neural Network Observer" @default.
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- W1546783933 hasPublicationYear "2011" @default.
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