Adaptive State Feedback Predictive Control and Expert Control for a Delayed Coking Furnace

张伟勇; 黄德先; 王毓栋; 王京春

doi:10.1016/S1004-9541(08)60126-3

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Adaptive State Feedback Predictive Control and Expert Control for a Delayed Coking Furnace

Updated：2026-01-06

- Adaptive State Feedback Predictive Control and Expert Control for a Delayed Coking Furnace
- Adaptive State Feedback Predictive Control and Expert Control for a Delayed Coking Furnace
- 中国化学工程学报（英文版） 2008年16卷第4期页码：590-598
- Affiliations：
  
  1. School of Information Science and Technology, Beijing University of Chemical Technology,Beijing,China,100029
  2. Department of Automation, Tsinghua University,Beijing,China,100084
  3. Tsinghua National Laboratory for Information Science and Technology,Beijing,China,100084
- Author bio：
- Funds：
  
  the State Key Development Program for Basic Research of China(2002CB312200);the National High Technology Research and Development Program of China(2007AA04Z193)
- DOI：10.1016/S1004-9541(08)60126-3
  中图分类号：
- 纸质出版：2008
- Accepted：
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张伟勇, 黄德先, 王毓栋, 等. Adaptive State Feedback Predictive Control and Expert Control for a Delayed Coking Furnace[J]. 中国化学工程学报（英文版）, 2008,16(4):590-598.

ZHANG Weiyong, HUANG Dexian, WANG Yudong, WANG Jingchun. Adaptive State Feedback Predictive Control and Expert Control for a Delayed Coking Furnace[J]. , 2008, 16(4): 590-598.
张伟勇, 黄德先, 王毓栋, 等. Adaptive State Feedback Predictive Control and Expert Control for a Delayed Coking Furnace[J]. 中国化学工程学报（英文版）, 2008,16(4):590-598. DOI： 10.1016/S1004-9541(08)60126-3.

ZHANG Weiyong, HUANG Dexian, WANG Yudong, WANG Jingchun. Adaptive State Feedback Predictive Control and Expert Control for a Delayed Coking Furnace[J]. , 2008, 16(4): 590-598. DOI： 10.1016/S1004-9541(08)60126-3.

摘要

Abstract

An adaptive state feedback predictive control (SFPC) scheme and an expert control scheme are presented and applied to the temperature control of a 1200 kt·a

-1

delayed coking furnace

which is the key equipment for the delayed coking process. Adaptive SFPC is used to improve the performance of temperature control in normal operation. A simplified nonlinear model on the basis of first principles of the furnace is developed to obtain a state space model by linearization. Taking advantage of the nonlinear model

an online model adapting method is presented to accommodate the dynamic change of process characteristics because of tube coking and load changes. To compensate the large inverse response of outlet temperature resulting from the sudden increase of injected steam of a particular velocity to tubes

a monitoring method and an expert control scheme based on heat balance calculation are proposed. Industrial implementation shows the effectiveness and feasibility of the proposed control strategy.

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