%0 Journal Article
%T LS-SVM predictive control based on PSO for nonlinear systems<br>基于粒子群优化的非线性系统最小二乘支持向量机预测控制方法
%A MU Chao-xu
%A ZHANG Rui-min
%A SUN Chang-yin
%A <br>穆朝絮
%A 张瑞民
%A 孙长银
%J 控制理论与应用
%D 2010
%I 
%X For the predictive control of nonlinear systems, we present a single-step predictive control algorithm based on model learning and particle swarm optimization(PSO). The method utilizes least square support vector machine(LSSVM) to estimate the model of a nonlinear system and forecast the output value, reducing the error in output feedback and error correction. The control values are obtained by the rolling optimization of PSO. This method can be used to design effective controllers for nonlinear systems with unknown mathematical models. For univariate and multivariate nonlinear systems, simulation results show that the predictive control algorithm is effective and has an excellent adaptive ability and robustness.
%K nonlinear systems
%K predictive control
%K least square support vector machine
%K particle swarm optimization<br>非线性系统
%K 预测控制
%K 最小二乘支持向量机
%K 粒子群
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=F94C300EC833C503CB99EB5EB9349375&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=0B39A22176CE99FB&sid=F260CE035846B3B8&eid=BBF7D98F9BEDEC74&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=1&reference_num=10