%0 Journal Article
%T Hybrid control based on sliding mode--dynamic recursive fuzzy neural network for marine electrical propulsion<br>滑模动态递归模糊神经网络船电推进复合控制
%A ZHANG Gui-chen
%A MA Jie
%A <br>张桂臣
%A 马捷
%J 控制理论与应用
%D 2011
%I 
%X We propose a hybrid control(HC) strategy for the marine electrical podded propulsion system to eliminate the overshoot and obtain a fast and smooth dynamic response for the podded propulsion. HC consists of a robust sliding mode control(SMC) and a dynamic recursive fuzzy neural network control(DRFNNC). SMC uses the dead-zone nonlinearity and error band method to tackle uncertainties and external disturbances; DRFNNC which has online self-learning algorithm forces the tracking error to approach zero. We build the hardware-in-loop simulation system of Siemens-Schottel-Propulsor(SSP) based on SIMOTION; the simulation and experimental results show that HC provides a fast and smooth dynamic response in both transient state and steady state, and improves the robustness and motion precision of the SSP system.
%K hybrid control
%K robust sliding mode
%K dynamic recursive fuzzy neural network
%K marine electrical propulsion
%K podded propulsion<br>复合控制
%K 鲁棒滑模
%K 动态递归模糊神经网络
%K 船舶电力推进
%K 吊舱推进
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=5704D2E38E2B920F7E16890D51B454C4&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=94C357A881DFC066&sid=42FF82ADD37D41AA&eid=039DCCB9394D9766&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=18