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Mathematical Problems in Engineering
Volume 2014, Article ID 472815, 9 pages
Research Article

An Adaptive Nonlinear Control for Gyro Stabilized Platform Based on Neural Networks and Disturbance Observer

Fundamental Science on Novel Inertial Instrument & Navigation System Technology Laboratory, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

Received 3 July 2014; Revised 30 October 2014; Accepted 10 November 2014; Published 25 November 2014

Academic Editor: Vu Ngoc Phat

Copyright © 2014 Jiancheng Fang and Rui Yin. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In order to improve the tracking performance of gyro stabilized platform with disturbances and uncertainties, an adaptive nonlinear control based on neural networks and reduced-order disturbance observer for disturbance compensation is developed. First the reduced-order disturbance observer estimates the disturbance directly. The error of the estimated disturbance caused by parameter variation and measurement noise is then approximated by neural networks. The phase compensation is also introduced to the proposed control law for the desired sinusoidal tracking. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Experimental results show the validity of the proposed control approach.