引用本文:王定成, 方廷健.一种基于支持向量机的内模控制方法[J].控制理论与应用,2004,21(1):85~88.[点击复制]
WANG Ding-cheng, FANG Ting-jian.Internal model control approach based on support vector machines[J].Control Theory and Technology,2004,21(1):85~88.[点击复制]
一种基于支持向量机的内模控制方法
Internal model control approach based on support vector machines
摘要点击 1315  全文点击 1623  投稿时间：2002-03-18  修订日期：2003-04-18
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DOI编号  
  2004,21(1):85-88
中文关键词  支持向量机(SVM)  支持向量机回归(SVMR)  内模控制(IMC)  非线性
英文关键词  support vector machines (SVM)  SVMR  IMC  non-linear
基金项目  
作者单位
王定成, 方廷健 中国农业大学 精细农业研究中心,北京 100083
中国科学院 合肥智能机械研究所,安徽 合肥 230031 
中文摘要
      在基于数据的基础上,采用SVM回归理论建立系统的正向模型和设计逆模控制器.首先简要介绍了SVMR的原理,然后将其应用于内模控制问题,并建立了SVMR模型.其次,在控制过程可逆的条件下设计了SVMR控制器.最后将该控制方法应用于一可逆非线性系统和具未知干扰的温室环境控制问题,仿真结果表明该方法与神经网络IMC相比,具有较简单的模型和较好的控制性能.
英文摘要
      The system process was modeled and an inverse model controller using support vector machine regression (SVMR) was designed. First, the SVMR principle was briefly introduced. Second, the SVMR was applied to the internal model control (IMC) problem, and the SVMR internal model was developed. Third, an SVMR controller for internal model control problem was proposed under the inverse condition of control process. Finally, the control algorithm was applied to the reversible nonlinear system and greenhouse environment with unknown disturbance, and compared with neural networks IMC using simulation, and the results showed that the SVMR IMC has a simplified model and good control performance.