Self-optimizing control based on multi-objective optimization for heavy oil catalytic pyrolysis in two-stage riser

WANG Ping; ZHAO Hui; YANG Chaohe

doi:10.11949/j.issn.0438-1157.20160414

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Self-optimizing control based on multi-objective optimization for heavy oil catalytic pyrolysis in two-stage riser

更新时间：2025-12-10

- Self-optimizing control based on multi-objective optimization for heavy oil catalytic pyrolysis in two-stage riser
- CIESC Journal Issue 8, Pages: 3491-3498(2016)
- 作者机构：
  
  1. 中国石油大学(华东)重质油国家重点实验室,山东,青岛,266580
  2. 中国石油大学(华东)信息与控制工程学院,山东,青岛,266580
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20160414
  CLC： E624
- Online First：05 August 2016，
  
  Published：05 August 2016
- 稿件说明：
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WANG Ping, ZHAO Hui, YANG Chaohe. Self-optimizing control based on multi-objective optimization for heavy oil catalytic pyrolysis in two-stage riser[J]. CIESC Journal, 2016, (8): 3491-3498.
DOI：

WANG Ping, ZHAO Hui, YANG Chaohe. Self-optimizing control based on multi-objective optimization for heavy oil catalytic pyrolysis in two-stage riser[J]. CIESC Journal, 2016, (8): 3491-3498. DOI： 10.11949/j.issn.0438-1157.20160414.

摘要

针对两段提升管重油催化裂解过程经济运行要求和工艺特点，从多目标优化角度出发，提出一种自优化控制方法。首先，基于过程稳态模型，考虑操作约束条件，构造同时最大化丙烯产量和最小化干气产量的多目标操作优化问题，并采用标准化法向约束方法求解获得完整、均匀分布的Pareto最优解；然后，根据多目标优化结果所揭示的最优操作条件与积极约束之间的关系，提出了一种基于串级控制的自优化控制策略。仿真结果表明，与传统的提升管出口温度设定值跟踪控制相比，本文方法在干扰作用下能够及时调整操作条件，降低干扰对过程优化运行的不利影响。

Abstract

Considered economic requirement for maximizing propylene yield of fluidized catalytic pyrolysis process in two-stage riser

as well as complex characteristics of the FCC process such as strong nonlinearity

coupling multivariable and unavailability in online measurement of product yields

a self-optimizing control strategy on a basis of multi-objective optimization was proposed. First

a multi-objective optimization framework for maximizing propylene yield while minimizing dry gas output was created from steady state model and operational constraints of the process

and solved for optimal operation condition with a complete and uniform Pareto distribution by standardized normal constraint method. Secondly

a self-optimizing scheme of cascade controls was generated from relationships between the optimal operation condition and the active constraints. Product yield that could not be measured online were estimated by an unscented Kalman filter transformation. Compared to the tracking control on temperature setpoints at the riser outlet

the self-optimizing control method could spontaneously adjust operating condition under circumstances of interference and reduce the disadvantageous impact of noise factors to optimizing process operation.

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