%0 Journal Article
%T Sliding Mode Backstepping Control of Induction Motor Based on Self-recurrent Wavelet Neural Networks<br>基于自回归小波神经网络的感应电动机滑模反推控制
%A WANG Jia-Jun
%A <br>王家军
%J 自动化学报
%D 2009
%I 
%X A new decoupled induction motor model is introduced for enhancing the robustness of control. Sliding mode control and backstepping control are applied to virtual torque and flux linkage voltage controller designs based on induction motor decoupled model. The magnitude of sliding mode switching gain is the key reason causing system chattering. Self-recurrent wavelet neural networks (SRWNN) is used to estimate sliding mode switching gain on-line, which can reduce chattering caused by sliding mode control effectively. The results of simulation prove that the scheme of sliding mode backstepping control based on SRWNN on-line estimation of switching gain can enhance the robustness of induction motor control effectively and reduce the chattering caused by sliding mode control as well.
%K Induction motor
%K self-recurrent wavelet neural networks (SRWNN)
%K sliding mode control
%K backstepping control<br>感应电动机
%K 自回归小波神经网络
%K 滑模控制
%K 反推控制
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=3565EB671BEC47DD69E064F236950E56&yid=DE12191FBD62783C&vid=6209D9E8050195F5&iid=CA4FD0336C81A37A&sid=CA4FD0336C81A37A&eid=5D311CA918CA9A03&journal_id=0254-4156&journal_name=自动化学报&referenced_num=0&reference_num=22