%0 Journal Article %A ZHAI Yong-jie %A LI Hai-li %A WANG Dong-feng %A HAN Pu %T Generalized predictive control using LS-SVM error compensation %D 2010 %R 10.3778/j.issn.1002-8331.2010.03.059 %J Computer Engineering and Applications %P 192-194 %V 46 %N 3 %X Learning the multi-step forecast optimization strategy from Dynamic Matrix Control(DMC) and Model Algorithmic Control(MAC),Generalized Predictive Control(GPC) has a strong ability to overcome load disturbance,random noise and delay change,and the selected model has less parameters,so it is easy to control.However,according to research,GPC has some limitations in the problem of model mismatch.LS-SVM is developed based on Support Vector Machines,and has sound functions in regression and classification.On the basis of conscientiously studying the Least Squares Support Vector Machine(LS-SVM) principle,the GPC based on LS-SVM error compensation is proposed,and is simulated on two models.From the comparison with the conventional GPC,it proves that the algorithm had better performances in control. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2010.03.059