Temperature prediction control based on least squares support vector machines
Bin Liu
Hongye SU
Weihua HUANG
Jian CHU
摘要：A prediction control algorithm is presented based on least squares support vector machines (LS-SVM) model for a class of complex systems with strong nonlinearity.The nonlinear off-line model of the controlled plant is built by LS-SVM with radial basis function (RBF) kernel.In the process of system running,the off-line model is linearized at each sampling instant,and the generalized prediction control (GPC) algorithm is employed to implement the prediction control for the controlled plant.The obtained algorithm is applied to a boiler temperature control system with complicated nonlinearity and large time delay.The results of the experiment verify the effectiveness and merit of the algorithm.
机标关键词：support vector machinesgeneralized prediction controltemperature control systemradial basis functioncontrol algorithmcomplex systemsleast squarestime delay
分类号：O1(数学)
资助基金：国家杰出青年科学基金(60025308)
论文发表日期：2004-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：6( 365-370 )
英文信息