全局自优化控制策略及其测量变量子集选择

doi:10.11949/0438-1157.20200871

摘要/Abstract

摘要：

针对过程系统的优化运行问题，介绍一种基于Monte Carlo模拟的全局自优化控制策略。利用非线性模型计算整个操作空间内的平均经济损失，通过对某些条件进行合理假设，得到全局被控变量的解析表达形式。为了平衡传感器成本和系统性能，在全局自优化控制策略的基础上，引入混合整数约束，对测量变量子集进行选择。通过求解混合整数规划问题，能够同时获得最优的测量变量子集以及由其构成的全局被控变量，此外上述子集选择方法还可以处理附加的结构性约束问题。通过对蒸发过程的研究表明，该方法可以更加高效地处理测量变量子集选择问题，通过对精馏塔案例的研究，进一步验证了该方法在处理结构性约束问题中的优势。

关键词: 过程系统, Monte Carlo模拟, 自优化控制, 非线性模型, 优化, 混合整数约束, 子集选择

Abstract:

Aiming at the problem of optimal operation of the process system, a global self-optimizing control (SOC) strategy based on Monte Carlo simulation was introduced. The nonlinear model was employed to calculate the average economic loss over the entire operating space. Reasonable assumptions were made for some conditions, and the analytical solution of the controlled variables (CVs) was obtained. Besides, mixed integer constraints were incorporated into the global SOC strategy with the aim of balancing the sensor investment and control system performance. The proposed method can handle additional structural constraints as well as determine the optimal subset of measurements with globally valid CVs. An evaporation process was investigated to show the effectiveness of dealing with the measurement subset selection, and a distillation column case was studied to illustrate the advantages of handling the structural constraints problem.

Key words: process systems, Monte Carlo simulation, self-optimizing control, nonlinear model, optimization, mixed integer constraints, subset selection

中图分类号:

李啸晨, 苏宏业, 谢磊, 王一钦. 全局自优化控制策略及其测量变量子集选择[J]. 化工学报, 2021, 72(3): 1585-1594.

LI Xiaochen, SU Hongye, XIE Lei, WANG Yiqin. Research on the measurement subset selection for global self-optimizing control strategy[J]. CIESC Journal, 2021, 72(3): 1585-1594.

图/表 7

参考文献 32

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变量名称	物理含义	标称值	单位
F₁	进料质量流量	10.000	kg/min
F₂	产物质量流量	1.334	kg/min
F₃	循环质量流量	24.721	kg/min
F₄	气相质量流量	8.135	kg/min
F₅	冷凝液质量流量	8.135	kg/min
X₁	进料摩尔分数	5.000	%
X₂	产物摩尔分数	35.000	%
T₁	进料温度	40.000	℃
T₂	产物温度	88.400	℃
T₃	气相温度	81.066	℃
L₂	分离器液位	1.000	m
P₂	操作压力	51.412	kPa
F₁₀₀	蒸汽质量流量	9.434	kg/min
T₁₀₀	蒸汽温度	151.520	℃
P₁₀₀	蒸汽压力	400.000	kPa
Q₁₀₀	热负荷	345.292	kW
Q₂₀₀	冷却器热负荷	313.210	kW
F₂₀₀	冷却水质量流量	217.738	kg/min
T₂₀₀	冷却水入口温度	25.000	℃
T₂₀₁	冷却水出口温度	45.550	℃

变量名称	物理含义	标称值	单位
F₁	进料质量流量	10.000	kg/min
F₂	产物质量流量	1.334	kg/min
F₃	循环质量流量	24.721	kg/min
F₄	气相质量流量	8.135	kg/min
F₅	冷凝液质量流量	8.135	kg/min
X₁	进料摩尔分数	5.000	%
X₂	产物摩尔分数	35.000	%
T₁	进料温度	40.000	℃
T₂	产物温度	88.400	℃
T₃	气相温度	81.066	℃
L₂	分离器液位	1.000	m
P₂	操作压力	51.412	kPa
F₁₀₀	蒸汽质量流量	9.434	kg/min
T₁₀₀	蒸汽温度	151.520	℃
P₁₀₀	蒸汽压力	400.000	kPa
Q₁₀₀	热负荷	345.292	kW
Q₂₀₀	冷却器热负荷	313.210	kW
F₂₀₀	冷却水质量流量	217.738	kg/min
T₂₀₀	冷却水入口温度	25.000	℃
T₂₀₁	冷却水出口温度	45.550	℃

变量数量	最优测量变量子集	平均损失
4	[P₂T₂T₃F₅]	2.6508
5	[P₂T₂T₃F₁₀₀F₅]	2.0517
6	[P₂T₂T₃ F₁₀₀T₂₀₁F₅]	2.0386
7	[P₂T₂T₃F₁₀₀F₃F₅ F₁]	1.9650
8	[P₂T₂T₃F₁₀₀T₂₀₁F₃F₅F₁]	1.9361
9	[P₂T₂T₃F₁₀₀T₂₀₁F₃F₅F₂₀₀F₁]	1.9188
10	[P₂T₂T₃F₂F₁₀₀T₂₀₁F₃F₅F₂₀₀F₁]	1.9014

变量数量	最优测量变量子集	平均损失
4	[P₂T₂T₃F₅]	2.6508
5	[P₂T₂T₃F₁₀₀F₅]	2.0517
6	[P₂T₂T₃ F₁₀₀T₂₀₁F₅]	2.0386
7	[P₂T₂T₃F₁₀₀F₃F₅ F₁]	1.9650
8	[P₂T₂T₃F₁₀₀T₂₀₁F₃F₅F₁]	1.9361
9	[P₂T₂T₃F₁₀₀T₂₀₁F₃F₅F₂₀₀F₁]	1.9188
10	[P₂T₂T₃F₂F₁₀₀T₂₀₁F₃F₅F₂₀₀F₁]	1.9014

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