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| Temperature prediction control based on least squares support vector machines | |
| 作者姓名： | Bin LIU Hongye SU Weihua HUANG Jian CHU |
| 作者单位： | [1]NationalLaboratoryofIndustrialControlTechnology,InstituteofAdvancedProcessControl,ZhejiangUniversity,YuquanCampus,HangzhouZhejiang310027,China [2]DepartmentofAutomation,CollegeofInformationScienceandEngineering,WuhanUmversityofScienceandTechnology,WuhanHubei430081,China |
| 基金项目： | This work has been supported by the National Outstanding Youth Science Foundation of China (No. 60025308) and the Teach and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of MOE,China. |
| 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 controUed 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. |
| 关 键 词： | 预测控制 最小二乘方支持向量机 RBF核函数 广义预测 |
| 收稿时间： | 28 April 2004 |
| 修稿时间： | 2004/9/22 0:00:00 |
Temperature prediction control based on least squares support vector machines |
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| Bin LIU,Hongye SU,Weihua HUANG,Jian CHU.Temperature prediction control based on least squares support vector machines[J].Journal of Control Theory and Applications,2004,2(4):365-370. | |
| Authors: | Bin LIU Hongye SU Weihua HUANG Jian CHU |
| Affiliation: | 1. National Laboratory of Industrial Control Technology,Institute of Advanced Process Control,Zhejiang University,Yuquan Campus,Hangzhou Zhejiang 310027,China;Department of Automation,College of Information Science and Engineering,Wuhan University of Science 2. National Laboratory of Industrial Control Technology,Institute of Advanced Process Control,Zhejiang University,Yuquan Campus,Hangzhou Zhejiang 310027,China 3. Department of Automation,College of Information Science and Engineering,Wuhan University of Science and Technology,Wuhan Hubei 430081,China |
| Abstract: | 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. |
| Keywords: | Predictive control Least squares support vector machines RBF kernel function Generalized prediction control |
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