Gradient information-based strategy for real time optimization and control integration

被引：0
|
作者：
Li X.-C. [1 ]
Su H.-Y. [1 ]
Shao H.-S. [1 ]
Xie L. [1 ]
机构：
[1] Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou
来源：
Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2019年 / 53卷 / 05期
关键词：
Cascade structure; Controlled variables; Gradient information; Hierarchy model; Least square; Optimal operation;
D O I：
10.3785/j.issn.1008-973X.2019.05.004
中图分类号：
学科分类号：
摘要：
The hierarchy model of process system was analyzed, and the cascade structure of real time optimization and control integration was proposed, aiming at the optimal operation problem for industrial process. Gradient information-based steady state real time optimization approach was installed in the optimization layer. The setpoint was updated by collecting measurements online and estimating the gradient information of process. The proposed approach can effectively suppress the impact of plant model mismatch on optimization objective, since it avoided using an explicit process model. A least square thought was introduced to compute the gradient vector. The proposed algorithm not only had a low computational burden, but also can be applied to the steady state real time optimization of large-scale industrial processes. A method for selecting controlled variables of nonlinear process was discussed. The proposed method minimized the global average loss based on the nonlinear model. Reasonable assumptions were made for some conditions, so that the suboptimal solution was obtained, in order to solve the nonlinear programming problem efficiently. The analytical solution of controlled variables was given and the calculation efficiency was improved as well as the optimization layer was connected with the control layer. A numerical example, evaporation process and exothermic reaction process were studied to illustrate the effectiveness of the proposed method. © 2019, Zhejiang University Press. All right reserved.
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页码：843 / 851and888
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