PROJECT TITLE :

Autonomous Flight of the Rotorcraft-Based UAV Using RISE Feedback and NN Feedforward Terms

ABSTRACT :

A footing tracking management system is developed for a rotorcraft-based unmanned aerial vehicle (RUAV) using sturdy integral of the signum of the error (RISE) feedback and neural network (NN) feedforward terms. While the standard NN-based adaptive controller guarantees uniformly ultimately bounded stability, the proposed NN-based adaptive control system guarantees semi-world asymptotic tracking of the RUAV using the RISE feedback control. The developed management system consists of an inner-loop and outer-loop. The inner-loop control system determines the perspective of the RUAV based mostly on an adaptive NN-based mostly linear dynamic model inversion (LDI) method with the RISE feedback. The outer-loop management system generates the angle reference love the given position, velocity, and heading references, and controls the altitude of the RUAV by the LDI method with the RISE feedback. The linear model for the LDI is obtained by a linearization of the nonlinear RUAV dynamics throughout hover flight. Asymptotic tracking of the perspective and altitude states is proven by a Lyapunov-based mostly stability analysis, and a numerical simulation is performed on the nonlinear RUAV model to validate the effectiveness of the controller.


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