| 引用本文: | 黄碧璇,毛志忠,贾润达.草酸钴合成过程批次间自适应优化[J].控制理论与应用,2016,33(2):189~195.[点击复制] |
| HUANG Bi-xuan,MAO Zhi-zhong,Jia Run-da.A batch-to-batch adaptive optimization for the cobalt oxalate synthesis process[J].Control Theory and Technology,2016,33(2):189~195.[点击复制] |
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| 草酸钴合成过程批次间自适应优化 |
| A batch-to-batch adaptive optimization for the cobalt oxalate synthesis process |
| 摘要点击 2828 全文点击 1613 投稿时间：2015-02-17 修订日期：2015-08-08 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 10.7641/CTA.2016.50145 |
| 2016,33(2):189-195 |
| 中文关键词 草酸钴合成过程 数据模型 自适应修正项 批次间优化 模型不确定性 |
| 英文关键词 cobalt oxalate synthesis process data models modifier-adaptation batch-to-batch optimization model uncertainty |
| 基金项目 国家自然科学基金项目(61473072, 61203103)资助. |
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| 中文摘要 |
| 本文以钴湿法冶金过程草酸钴合成为背景, 研究基于多向偏最小二乘回归(MPLS)模型的草酸钴平均粒度
批次间自适应优化策略. 本文首先利用MPLS方法建立草酸钴平均粒度的数据模型; 针对模型不确定性情况下难以
获得最优操作变量的问题, 提出利用批次间修正项自适应优化方法, 使迭代优化结果逐渐趋向于实际最优值; 本文
还通过引入T2统计量软约束将优化结果限制在数据模型的有效区间之内. 数值仿真表明该方法可以有效解决草酸
钴合成过程的批次间自适应优化问题, 且与传统两步方法和迭代学习控制相比具有更好的优化效果. |
| 英文摘要 |
| This paper takes the background of cobalt oxalate synthesis in cobalt hydrometallurgy process, and an adaptation
optimization strategy for mean particle size of cobalt oxalate based on multi-way partial least squares (MPLS) model
is studied. Firstly, the MPLS algorithm is used to build the data model of mean particle size of cobalt oxalate. In order
to overcome the problem that it is difficult to obtain the optimal manipulated variables under model uncertainty, a
modifier-adaptation strategy based batch-to-batch optimization method is proposed to make the iteration results converge
to the practical optimal operating point. Additionally, T2 statistic soft constraint is used to confine the optimal solution in
the valid region of the data-driven model. The simulation results show that the proposed method can efficiently solve the
batch-to-batch adaptation optimization problem for cobalt oxalate synthesis process, and better optimization results can be
achieved compared with traditional two-step approach and iterative learning control (ILC). |