%0 Journal Article
%T Adaptive neural control of uncertain nonholonomic systems with unknown virtual control coefficients<br>虚拟控制系数未知的非完整系统的自适应神经网络控制
%A YUAN Zhan-ping
%A WANG Zhu-ping
%A CHEN Qi-jun
%A <br>袁占平
%A 王祝萍
%A 陈启军
%J 控制理论与应用
%D 2011
%I 
%X An adaptive neural network control is applied to nonholonomic systems in chain form, with unknown virtual control coefficients and strong drift nonlinearities. The Backstepping technique and state-scaling are employed in designing the adaptive neural network control laws. Nussbaum-type functions are used to solve the problem of the completely unknown control direction. The uniform ultimate boundedness of all signals in the closed-loop is guaranteed; and the systems states are proven to converge to a small neighborhood of zero. The control performance of the closed-loop system is achieved by appropriately choosing the design parameters. The proposed adaptive neural network control is free from the control singularity problem. An adaptive control-based switching strategy is used to overcome the uncontrollability problem associated with x0(t0) = 0. Simulation results are provided to show the effectiveness of the proposed approach.
%K neural network
%K adaptive control
%K Backstepping
%K nonholonomic systems<br>神经网络
%K 自适应控制
%K 反推法
%K 非完整系统
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=7001BC79376919BCD56D22936C7034B2&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=0B39A22176CE99FB&sid=C29816B2656377A7&eid=FEF02B4635FE8227&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=26