The Trajectory Tracking Control of fixed-wing UAV with Self-organizing Fuzzy Neural Network to Identify and Compensate the Modelling Uncertainties
DOI:
https://doi.org/10.5890/JVTSD.2019.03.007Abstract
Firstly, the dynamics model of fixed-wing UAV is given in the paper and an adaptive controller of the mode is designed based on dynamic inversion method, then a compensation strategy called SFNN-RC based on the self-organizing fuzzy neural network techniques and a robust controller is designed to online identify and compensate the modeling uncertainty part of fixed-wing UAV system in trajectory tracking control process. The robust controller in SFNN-RC is presented to optimize the convergence performance of the self-organizing fuzzy neural network. The stability of the SFNN-RC method can be proved based on Lyapunov theory. To demonstrate the effectiveness of the proposed method, some simulation results are illustrated in this paper.References
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