Control of Three-Axis Gimbal in Unmanned Aerial Vehicles using Radial Basis Function Neural Network
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Abstract
This paper focuses on the modeling and control of a three-axis gimbal (TAG) in unmanned aerial vehicles (UAVs). An adaptive sliding control mode was synthesized using the Radial Basis Function (RBF) neural network for the TAG model. MATLAB Simulink software was used to simulate the operation of the TAG control system. The simulation of the operation of the system for tracking the location of the spacecraft and the movement of the spacecraft under the influence of unknown external forces has been performed. An assessment of the performance of the control system of the TAG, which is under the influence of random interference, is given.
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