Adaptive Control with Neural Networks-based Disturbance Observer for a Spherical UAV

被引：17

作者：

Matassini, Tommaso ^{[1
]}

Shin, Hyo-Sang ^{[2
]}

Tsourdos, Antonios ^{[2
]}

Innocenti, Mario ^{[1
]}

机构：

[1] Univ Pisa, Pisa, Italy

[2] Cranfield Univ, Cranfield, Beds, England

来源：

IFAC PAPERSONLINE | 2016年 / 49卷 / 17期

关键词：

Spherical UAV; model uncertainties and external disturbances; disturbance observer; adaptive control; neural networks;

D O I：

10.1016/j.ifacol.2016.09.053

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper develops a control scheme for a Spherical Unit voted Aerial Vehicle (UAV) which can be used in complex scenarios where traditional navigation and communications systems would not succeed. The proposed scheme is based on the nonlinear control theory combined with Adaptive Neural-Networks Disturbance Observer (NN-DOB) and controls the attitude and altitude of the UAV in presence of model uncertainties and external disturbances. The NN-DOB can effectively estimate the uncertainties without the knowledge of their bounds and the control system stability is proven using Lyapunov's stability theorems. Numerical simulation results demonstrate the validity of the proposed method on the LAY under model uncertainties and external disturbances. (C) 2016, I VAC (International Federation of Automatic Control) Hosting by Elsevier Ltd All rights reserved.

引用

页码：308 / 313

页数：6

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