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Gain adaptive sliding mode controller based on interval type-II fuzzy neural network designed for attitude control for micro aircraft vehicle

Xiangjian Chen (School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China)
Di Li (The 723 Institute of China Shipbuilding Industry Corporation (CSIC), Yangzhou, Jiangsu, China)
Zhijun Xu (Chang Chun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China)
Yue Bai (Chang Chun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China)

International Journal of Intelligent Computing and Cybernetics

ISSN: 1756-378X

Article publication date: 3 June 2014

190

Abstract

Purpose

Micro aerial vehicle is nonlinear plant; it is difficult to obtain stable control for MAV attitude due to uncertainties. The purpose of this paper is to propose one robust stable control strategy for MAV to accommodate system uncertainties, variations, and external disturbances.

Design/methodology/approach

First, by employing interval type-II fuzzy neural network (ITIIFNN) to approximate the nonlinearity function and uncertainty functions in the attitude angle dynamic model of micro aircraft vehicle (MAV). Then, the Lyapunov stability theorem is used to testify the asymptotic stability of the closed-loop system, the parameters of the ITIIFNN and gain of sliding mode control can be tuned on-line by adaptive laws based on Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system.

Findings

The validity of the proposed control method has been verified through real-time experiments. The experimental results show that the performance of interval type-II fuzzy neural network based gain adaptive sliding mode controller (GASMC-ITIIFNN) is significantly improved compared with conventional adaptive sliding mode controller (CASMC), type-I fuzzy neural network based sliding mode controller (GASMC-TIFNN).

Practical implications

This approach has been used in one MAV, the controller works well, and which could guarantee the MAV control system with good performances under uncertainties, variations, and external disturbances.

Originality/value

The main original contributions of this paper are: the proposed control scheme makes full use of the nominal model of the MAV attitude control model; the overall closed-loop control system is globally stable demonstrated by Lyapunov stable theory; the tracking error can be asymptotically attenuated to a desired small level around zero by appropriate chosen parameters and learning rates; and the MAV attitude control system based on GASMC-ITIIFNN controller can achieve favourable tracking performance than GASMC-TIFNN and CASMC.

Keywords

Citation

Chen, X., Li, D., Xu, Z. and Bai, Y. (2014), "Gain adaptive sliding mode controller based on interval type-II fuzzy neural network designed for attitude control for micro aircraft vehicle", International Journal of Intelligent Computing and Cybernetics, Vol. 7 No. 2, pp. 209-226. https://doi.org/10.1108/IJICC-03-2012-0010

Publisher

:

Emerald Group Publishing Limited

Copyright © 2014, Emerald Group Publishing Limited

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