Optimized neural network based sliding mode control for quadrotors with disturbances

Optimized neural network based sliding mode control for quadrotors with disturbances

In this paper, optimized radial basis function neural networks (RBFNNs) are employed to construct a sliding mode control (SMC) strategy for quadrotors with unknown disturbances. At first, the dynamics model of the controlled quadrotor is built, where some unknown external disturbances are considered...

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Bibliographic Details
Main Authors: Ping Li, Zhe Lin, Hong Shen, Zhaoqi Zhang, Xiaohua Mei
Format: Article
Language:English
Published: AIMS Press 2021-04-01
Series:Mathematical Biosciences and Engineering
Subjects:
quadrotor
sliding mode control (smc)
radial basis function neural network (rbfnn)
particle swarm optimization (pso)
disturbance
Online Access:http://www.aimspress.com/article/doi/10.3934/mbe.2021092?viewType=HTML

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