| 引用本文: | 孙 磊,金晓明.基于子空间辨识的模型预测控制策略及其应用[J].控制理论与应用,2009,26(3):313~315.[点击复制] |
| SUN Lei,JIN Xiao-ming.Model-predictive-control based on subspace identification and its application[J].Control Theory and Technology,2009,26(3):313~315.[点击复制] |
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| 基于子空间辨识的模型预测控制策略及其应用 |
| Model-predictive-control based on subspace identification and its application |
| 摘要点击 2189 全文点击 1742 投稿时间：2007-07-09 修订日期：2008-09-18 |
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| DOI编号 10.7641/j.issn.1000-8152.2009.3.017 |
| 2009,26(3):313-315 |
| 中文关键词 子空间辨识 自适应控制 匹配误差 模拟移动床 |
| 英文关键词 subspace identification adaptive control matching error simulated moving bed |
| 基金项目 国家高技术研究发展计划(2007AA041403). |
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| 中文摘要 |
| 针对化工过程中普遍存在的非线性和时变特性, 提出了一种基于递推子空间辨识的自适应预测控制策略.用子空间辨识法得到的预测模型作为初始模型, 通过比较初始模型和在线更新模型的匹配误差, 选择匹配误差较小的预测模型计算过程的输入, 从而提高了模型精度. 通过模拟移动床过程控制的仿真试验, 表明该方法具有较强的鲁棒性和抗干扰能力. |
| 英文摘要 |
| To deal with the nonlinearity and time-varying characteristics in the processes of chemical industry, an adaptive-predictive-control strategy based on the recursive subspace identification is proposed. The predictive models obtained from the subspace identification are considered the initial models, which are compared with the online updated model to generate matching errors. The model with the smallest matching error is selected for use in calculating the process control input, thus improving the model accuracy. The control simulations of a simulated moving bed(SMB) show that the method is robust to the system parameters perturbation and efficient in attenuating external disturbance. |