%0 Journal Article
%T Probabilistic robustness analysis of uncertain control systems using adaptive importance sampling<br>不确定控制系统概率鲁棒性分析——自适应重要抽样法
%A WU Huai-ning
%A CAI Kai-yuan
%A <br>吴淮宁
%A 蔡开元
%J 控制理论与应用
%D 2004
%I 
%X Adaptive importance sampling (AIS) method is applied to probabilistic robustness analysis problem of uncertain control systems,in order to overcome the difficulty that the standard Monte Carlo simulation (MCS) method cannot efficiently deal with rare events.A new AIS scheme is presented.First,a recursive algorithm estimating conditional mode was employed to generate a set of uncertain parameter vector samples which lead to instability or unacceptable performance of systems.And then,the subsequent iterative simulation procedures were taken with initial Gaussian importance sampling density function whose parameters were estimated by using this set of samples.Simulation results were provided to verify the effectiveness of the proposed method.
%K uncertain control systems
%K robustness analysis
%K probabilistic approach
%K importance sampling
%K Monte Carlo simulation<br>不确定控制系统
%K 鲁棒性分析
%K 概率方法
%K 重要抽样
%K MonteCarlo仿真
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=C9774BB1AAC9C12B&yid=D0E58B75BFD8E51C&vid=659D3B06EBF534A7&iid=94C357A881DFC066&sid=525CF7714FCB18E2&eid=43AADF4B53A8BF6F&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=1&reference_num=13