| Support vector regression-based internal model control |
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| 作者姓名： | 黄宴委 彭铁根 |
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| 作者单位： | Dept.of Automation Shanghai Jiaotong University，Dept.of Automation，Shanghai Jiaotong University，Shanghai 200030，China，Shanghai 200030，China |
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| 摘 要： | This paper proposes a design of internal model control systems for process with delay by using support vector regression(SVR).The proposed system fully uses the excellent nonlinear estimation performance of SVR with the structural risk minimization principle.Closed-system stability and steady error are analyzed for the existence of modeling errors.The simulations show that the proposed control systems have the better control performance than that by neural networks in the cases of the training samples with small size and noises.
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| 关 键 词： | 内模控制 支持向量机 神经网络 固有误差 稳定性 |
| 文章编号： | 1005-9113（2007）03-0411-04 |
| 修稿时间： | 2004-05-18 |
Support vector regression-based internal model control |
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| HUANG Yan-wei,PENG Tie-gen.Support vector regression-based internal model control[J].Journal of Harbin Institute of Technology,2007,14(3):411-414. |
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| Authors: | HUANG Yan-wei PENG Tie-gen |
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| Abstract: | This paper proposes a design of internal model control systems for process with delay by using support vector regression(SVR).The proposed system fully uses the excellent nonlinear estimation performance of SVR with the structural risk minimization principle.Closed-system stability and steady error are analyzed for the existence of modeling errors.The simulations show that the proposed control systems have the better control performance than that by neural networks in the cases of the training samples with small size and noises. |
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| Keywords: | internal model control support vector machine neural networks steady error stability |
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