基于分段线性化法的改进自主优化控制

叶凌箭; 钟伟红; 宋执环

doi:10.3724/SP.J.1004.2013.01231

基于分段线性化法的改进自主优化控制

doi: 10.3724/SP.J.1004.2013.01231

1.
浙江大学宁波理工学院宁波 315100;
2.
浙江大学工业控制技术国家重点实验室杭州 310027

基金项目:

国家重点基础研究发展计划(973计划) (2012CB720505);浙江省自然科学基金(LQ13F030007);宁波市创新团队(2012B82002) 资助

详细信息

作者简介:
叶凌箭浙江大学宁波理工学院讲师.分别于2006 年和2011 年获得浙江大学化工系学士和控制系博士学位. 主要研究方向为控制结构设计, 过程监测.E-mail: ljye@iipc.zju.edu.cn

计量
- 文章访问数: 2090
- HTML全文浏览量: 95
- PDF下载量: 1077
- 被引次数: 0
出版历程
- 收稿日期: 2012-05-24
- 修回日期: 2012-11-26
- 刊出日期: 2013-08-20

Improved Self-optimizing Control Method Based on Piece-wise Linearization

1.
Ningbo Institute of Technology, Zhejiang University, Ningbo 315100;
2.
State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027

Funds:

Supported by National Basic Research Program of China (973 Program) (2012CB720505), Zhejiang Provincial Natural Science Foundation (LQ13F030007), and Ningbo Innovation Team (2012 B82002)

摘要

摘要: 现有自主优化控制方法(Self-optimizing control, SOC)均基于系统名义工作点的线性化模型,过程的非线性较强时, 由线性化误差导致的损失将显著影响控制系统的自主优化性能.提出了一种基于分段线性化模型的改进自主优化控制方法, 获取不同扰动工况下的分段线性化模型,分别应用线性化SOC方法并构造总的被控变量. 新方法能够在更大范围的操作空间内最小化平均损失,具有更加优异的自主优化效果. 对一个数值算例和一个放热反应过程的研究验证了提出方法的有效性.
- 自主优化 /
- 分段线性化 /
- 被控变量 /
- 优化控制
Abstract: The existing self-optimizing control (SOC) methods are all based on the linearized model around the nominal point, which may cause big objective function loss due to linearization error when the process is highly nonlinear. This paper presents an improved SOC method based on piece-wise linearization. Piece-wise linearized models are obtained at different operation points, then the linear SOC method is applied and the controlled variables are synthesized finally. The new method minimizes the average loss in a wider range hence the self-optimizing performance is better. A numerical case and an exothermic reactor are studied to demonstrate the usage of the proposed method.
- Self-optimizing control SOC /
- piece-wise linearization /
- controlled variables /
- optimal control

HTML全文

参考文献(15)

[1]	Skogestad S. Plantwide control: the search for the self-optimizing control structure. Journal of Process Control, 2000, 10(5): 487-507
[2]	Morari M, Arkun Y, Stephanopoulos G. Studies in the synthesis of control structures for chemical processes: Part 1: formulation of the problem. Process decomposition and the classification of the control tasks. Analysis of the optimizing control structures. AIChE Journal, 1980, 26(2): 220-232
[3]	Skogestad S. Control structure design for complete chemical plants. Computers and Chemical Engineering, 2004, 28(1-2): 219-234
[4]	Larsson T, Govatsmark M S, Skogestad S, Yu C C. Control structure selection for reactor, separator, and recycle processes. Industrial and Engineering Chemistry Research, 2003, 42(6): 1225-1234
[5]	Larsson T, Hestetun K, Hovland E, Skogestad S. Self-optimizing control of a large-scale plant: the Tennessee Eastman process. Industrial and Engineering Chemistry Research, 2001, 40(22): 4889-4901
[6]	Jagtap R, Kaistha N, Skogestad S. Plantwide control for economic optimum operation of a recycle process with side reaction. Industrial and Engineering Chemistry Research, 2011, 50(14): 8571-8584
[7]	de Araújo A C B, Gallani S, Mulas M, Olsson G. Systematic approach to the design of operation and control policies in activated sludge systems. Industrial and Engineering Chemistry Research, 2011, 50(14): 8542-8557
[8]	Halvorsen I J, Skogestad S, Morud J C, Alstad V. Optimal selection of controlled variables. Industrial and Engineering Chemistry Research, 2003, 42(14): 3273-3284
[9]	Kariwala V. Optimal measurement combination for local self-optimizing control. Industrial and Engineering Chemistry Research, 2007, 46(11): 3629-3634
[10]	Kariwala V, Cao Y, Janardhanan S. Local self-optimizing control with average loss minimization. Industrial and Engineering Chemistry Research, 2008, 47(4): 1150-1158
[11]	Alstad V, Skogestad S. Null space method for selecting optimal measurement combinations as controlled variables. Industrial and Engineering Chemistry Research, 2007, 46(3): 846-853
[12]	Alstad V, Skogestad S, Hori E S. Optimal measurement combinations as controlled variables. Journal of Process Control, 2009, 19(1): 138-148
[13]	Ye Ling-Jian, Li Ying-Dao, Song Zhi-Huan. New approach for constructing controlled variables for chemical processes. CIESC Journal, 2011, 62(8): 2221-2226 (叶凌箭, 李英道, 宋执环. 一种构造化工过程被控变量的方法. 化工学报, 2011, 62(8): 2221-2226)
[14]	Edgar T F, Himmelblau D M, Lasdon L S. Optimization of Chemical Processes (2nd edition). Boston: McGraw-Hill, 2001
[15]	Jäschke J, Skogestad S. NCO tracking and self-optimizing control in the context of real-time optimization. Journal of Process Control, 2011, 21(10): 1407-1416