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清华大学学报(自然科学版)  2019, Vol. 59 Issue (5): 403-408    DOI: 10.16511/j.cnki.qhdxxb.2019.22.002
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基于梯度特征的分布曲线模型预测控制算法
王鑫, 徐祖华, 赵均, 邵之江
浙江大学 控制科学与工程学院, 流程生产质量优化与控制国际联合研究中心, 杭州 310027
Gradient feature-based model predictive controlalgorithm of distribution processes
WANG Xin, XU Zuhua, ZHAO Jun, SHAO Zhijiang
National Center for International Research on Quality-Targeted Process Optimization and Control, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
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摘要 在分布曲线控制中,传统的积分平方误差指标仅考虑输出曲线与目标曲线的误差面积,忽略了分布曲线的内在特征结构。该文从曲线相似度度量出发,提出了一种基于梯度特征的分布曲线模型预测控制算法。该算法采用B样条模型描述分布曲线对象,基于梯度特征度量曲线相似度,综合曲线数值信息与梯度信息构造优化命题,并通过复合梯形方法对优化命题进行离散化,求解得到最优控制策略。仿真结果表明:该算法可提高曲线切换过程中输出曲线与目标曲线的相似度,实现了曲线形状的自然过渡。
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王鑫
徐祖华
赵均
邵之江
关键词 模型预测控制分布曲线曲线相似度梯度特征    
Abstract:In the control of distribution processes, the traditional integral square error performance index only considers the area between the output curve and the target curve, which ignores the structural features of the distribution curve. A gradient feature-based model predictive control algorithm that takes into account the curve similarities is developed for distribution processes. The algorithm first models the distribution process curve with B-splines. Then, the algorithm quantifies the similarity between the curves based on gradient features and optimizes the design by combining numerical and gradient information. The composite trapezoidal rule is then used to discretize the optimization proposition. Finally, the optimization proposition is solved to get the optimal solution. Simulations show that this algorithm improves the similarity between the output curve and the target curve during curve switching with natural transitions of the curve shape.
Key wordsmodel predictive control    distribution process    curve similarity    gradient feature
收稿日期: 2018-10-10      出版日期: 2019-05-14
基金资助:国家重点研发计划(2017YFB0603703);国家自然科学基金-浙江两化融合联合基金项目(U1509209);国家自然科学基金项目(61773340);中央高校基本科研业务费专项(2018QNA5011)
通讯作者: 徐祖华,副教授,E-mail:zhxu@zju.edu.cn     E-mail: zhxu@zju.edu.cn
引用本文:   
王鑫, 徐祖华, 赵均, 邵之江. 基于梯度特征的分布曲线模型预测控制算法[J]. 清华大学学报(自然科学版), 2019, 59(5): 403-408.
WANG Xin, XU Zuhua, ZHAO Jun, SHAO Zhijiang. Gradient feature-based model predictive controlalgorithm of distribution processes. Journal of Tsinghua University(Science and Technology), 2019, 59(5): 403-408.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2019.22.002  或          http://jst.tsinghuajournals.com/CN/Y2019/V59/I5/403
  图1 曲线相似度示例
  表1 两条曲线的相似度
  图2 目标曲线与 B样条基函数曲线
  图3 控制增量的能量曲线
  图4 控制输入响应曲线
  图5 GradientGMPC控制效果仿真结果
  图6 ISEGMPC控制效果仿真结果
  图7 曲线相似度变化对比
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