This study deals with the neuro-fuzzy (NF) modelling of a real industrial winding process in which the acquired NF model can be exploited to improve control performance and achieve a robust fault-tolerant system. A ne...This study deals with the neuro-fuzzy (NF) modelling of a real industrial winding process in which the acquired NF model can be exploited to improve control performance and achieve a robust fault-tolerant system. A new simulator model is proposed for a winding process using non-linear identification based on a recurrent local linear neuro-fuzzy (RLLNF) network trained by local linear model tree (LOLIMOT), which is an incremental tree-based learning algorithm. The proposed NF models are compared with other known intelligent identifiers, namely multilayer perceptron (MLP) and radial basis function (RBF). Comparison of our proposed non-linear models and associated models obtained through the least square error (LSE) technique (the optimal modelling method for linear systems) confirms that the winding process is a non-linear system. Experimental results show the effectiveness of our proposed NF modelling approach.展开更多
Y2000-62203-3023 0015560非线性稳定(含6篇论文)=FA03:Nonlinear stabiliza- tion[会,英]//1999 IEEE Proceedings of American Con-trol Conference,Vol.5 of 6.—3023～3050(NiD)本部分收录6篇论文,内容涉及非线性不确定系统的鲁棒...Y2000-62203-3023 0015560非线性稳定(含6篇论文)=FA03:Nonlinear stabiliza- tion[会,英]//1999 IEEE Proceedings of American Con-trol Conference,Vol.5 of 6.—3023～3050(NiD)本部分收录6篇论文,内容涉及非线性不确定系统的鲁棒开关控制器。展开更多
文摘This study deals with the neuro-fuzzy (NF) modelling of a real industrial winding process in which the acquired NF model can be exploited to improve control performance and achieve a robust fault-tolerant system. A new simulator model is proposed for a winding process using non-linear identification based on a recurrent local linear neuro-fuzzy (RLLNF) network trained by local linear model tree (LOLIMOT), which is an incremental tree-based learning algorithm. The proposed NF models are compared with other known intelligent identifiers, namely multilayer perceptron (MLP) and radial basis function (RBF). Comparison of our proposed non-linear models and associated models obtained through the least square error (LSE) technique (the optimal modelling method for linear systems) confirms that the winding process is a non-linear system. Experimental results show the effectiveness of our proposed NF modelling approach.
文摘Y2000-62203-3023 0015560非线性稳定(含6篇论文)=FA03:Nonlinear stabiliza- tion[会,英]//1999 IEEE Proceedings of American Con-trol Conference,Vol.5 of 6.—3023～3050(NiD)本部分收录6篇论文,内容涉及非线性不确定系统的鲁棒开关控制器。
