文章基本信息

标题：Robust kernel-based model reference adaptive control for unstable aircraft
本地全文：下载
作者：Zhao-Xu Yang ; Guang-She Zhao ; Rong-Jing Bao 等
期刊名称：Advances in Mechanical Engineering
印刷版ISSN：1687-8140
电子版ISSN：1687-8140
出版年度：2016
卷号：8
期号：11
DOI：10.1177/1687814016677207
语种：English
出版社：Sage Publications Ltd.
摘要：In this article, a robust kernel-based model reference adaptive control is proposed for an unstable nonlinear aircraft. The heart of the proposed kernel-based model reference adaptive control scheme comprises an offline neural identifier and an online neural controller. In the offline neural identifier, the kernel-based unified extreme learning machine algorithm is used to identify the aircraft model with the available input–output data in a finite time interval. The finite time interval is selected to avoid the response of the unstable aircraft growing unbounded. In the kernel-based unified extreme learning machine, the hidden layer feature mapping is determined by the kernel matrix. However, the unified extreme learning machine is a batch learning algorithm and is not suitable for the online control learning. To solve the problem, a recursive version of the unified extreme learning machine is developed in this study. Based on a given reference model and the identified model, the recursive version of the unified extreme learning machine algorithm is applied to construct the online control law to compensate for the changes in the aircraft dynamics or characteristics. The performance of the proposed kernel-based model reference adaptive control scheme is validated through the simulation studies of a locally nonlinear longitudinal high-performance aircraft. Simulation studies are also compared with a model reference adaptive control based on the back-propagation algorithm and a model reference adaptive control based on the basic extreme learning machine algorithm in terms of the identification and tracking abilities. The results show that the proposed kernel-based model reference adaptive control can achieve better identification and tracking performance.
关键词：Unified extreme learning machine; kernel-based; recursive; model reference adaptive control; unstable aircraft