基于动态矩阵控制的双层结构预测控制的整体解决方案

李世卿; 丁宝苍

doi:10.16383/j.aas.2015.c150126

基于动态矩阵控制的双层结构预测控制的整体解决方案

doi: 10.16383/j.aas.2015.c150126

李世卿,
丁宝苍^,

1.
西安交通大学电子与信息工程学院智能网络与网络安全教育部重点实验室西安 710049

基金项目:

国家高技术研究发展计划项目(863计划)(2014AA041802),国家自然科学基金项目(61174095)资助

详细信息

作者简介:
李世卿西安交通大学硕士研究生.主要研究方向为预测控制.E-mail:lsqjhy@126.com

通讯作者:
丁宝苍 2000年和2003年分别在中国石油大学(北京)和上海交通大学获得硕士、博士学位.曾为河北工业大学副教授、重庆大学教授.现为西安交通大学教授.主要研究方向为预测控制、模糊控制及其在流程工业中的应用.本文通信作者.E-mail:baocang.ding@gmail.com

计量
- 文章访问数: 2058
- HTML全文浏览量: 78
- PDF下载量: 1316
- 被引次数: 0
出版历程
- 收稿日期: 2015-03-11
- 修回日期: 2015-08-09
- 刊出日期: 2015-11-20

An Overall Solution to Double-layered Model Predictive Control Based on Dynamic Matrix Control

LI Shi-Qing,
DING Bao-Cang^,

1.
Ministry of Education Key Lab For Intelligent Networks and Network Security (MOE KLINNS), School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049

Funds:

Supported by National High-tech Research and Development Program of China (2014AA041802) and National Natural Science Foundation of China (61174095)

摘要

摘要: 本文给出一种双层结构预测控制的整体解决方案. 该方案分为开环预测、稳态目标计算和动态控制三个模块. 开环预测基于实测被控变量值和过去的操作变量值, 在假设未来操作变量不再变化的情况下, 估计未来的被控变量值. 稳态目标计算根据开环预测结果和外部目标等要求, 计算操作变量、被控变量的稳态目标值以及软约束的放松量. 动态控制根据开环预测结果和稳态目标输出结果, 计算未来的控制作用增量序列, 采用经典的动态矩阵控制策略. 这个整体解决方案保证了三个模块在模型、约束、目标上的一致性. 该算法是在已有文献的基础上, 将三个模块统一处理得到的. 仿真与应用例子证实了该算法的有效性.
- 预测控制 /
- 开环预测 /
- 稳态目标计算 /
- 动态矩阵控制
Abstract: This paper gives an overall solution to the double-layered model predictive control (MPC). This scheme includes three modules, i.e., the open-loop prediction, the steady-state target calculation (SSTC), and the dynamic control. Based on real-time output measurement and past inputs, the open-loop prediction module estimates the future outputs by assuming that the future inputs keep unchanged. Based on the open-loop predictions and the external targets, the SSTC module calculates the steady-state targets and the slacking values of the soft constraints. Then according to the open-loop predictions and SSTC results, the dynamic control module calculates the future control increments, which applies the classical dynamic matrix control (DMC). This overall solution guarantees the consistency of the three modules with respect to model, constraints and targets. Simulation and application examples have verified the effectiveness of the proposed algorithm.
- Model predictive control (MPC) /
- open-loop prediction /
- steady-state target calculation (SSTC) /
- dynamic matric control

HTML全文

参考文献(16)

[1]	席裕庚, 李德伟, 林姝. 模型预测控制现状与挑战. 自动化学报, 2013, 39(3):222-236(Xi Yu-Geng, Li De-Wei, Lin Shu. Model predictive controlstatus and challenges. Acta Automatica Sinica, 2013, 39(3):222-236)
[2]	[2] Darby M L, Nikolaou M. MPC:current practice and challenges. Control Engineering Practice, 2012, 20(4):328-342
[3]	[3] Ying C M, Joseph B. Performance and stability analysis of LP-MPC and QP-MPC cascade control systems. AIChE Journal, 1999, 45(7):1521-1534
[4]	邹涛, 李海强. 具有积分环节多变量系统的双层结构预测控制. 浙江大学学报(工学版), 2011, 45(12):2079-2087(Zou Tao, Li Hai-Qiang. Two-layer predictive control of multi-variable system with integrating element. Journal of Zhejiang University (Engineering Science), 2011, 45(12):2079-2087)
[5]	邹涛, 丁宝苍, 张端. 模型预测控制工程应用导论. 北京:化学工业出版社, 2010. (Zou Tao, Ding Bao-Cang, Zhang Duan. MPC:An Introduction to Industrial Applications. Beijing:Chemical Industry Press, 2010.)
[6]	钱积新, 赵均, 徐祖华. 预测控制. 北京:化学工业出版社, 2007. (Qian Ji-Xin, Zhao Jun, Xu Zu-Hua. Predictive Control. Beijing:Chemical Industry Press, 2007.)
[7]	席裕庚, 谷寒雨. 有约束多目标多自由度优化的可行性分析及软约束调整. 自动化学报, 1998, 24(6):727-732(Xi Yu-Geng, Gu Han-Yu. Feasibility analysis and soft constraints adjustment of CMMO. Acta Automatica Sinica, 1998, 24(6):727-732)
[8]	[8] Qin S J, Badgwell T A. A survey of industrial model predictive control technology. Control Engineering Practice, 2003, 11(7):733-764
[9]	[9] Rao C V, Rawlings J B. Steady states and constraints in model predictive control. AIChE Journal, 1999, 45(6):1266-1278
[10]	Nikandrov A, Swartz C L E. Sensitivity analysis of LP-MPC cascade control systems. Journal of Process Control, 2009, 19(1):16-24
[11]	Kassmann D E, Badgwell T A, Hawkins R B. Robust steady-state target calculation for model predictive control. AIChE Journal, 2000, 46(5):1007-1024
[12]	席裕庚. 复杂工业过程的满意控制. 信息与控制, 1995, 24(1):14-20(Xi Yu-Geng. Satisfactory control of complex industrial process. Information and Control, 1995, 24(1):14-20)
[13]	潘红光, 高海南, 孙耀, 张英, 丁宝苍. 基于多优先级稳态优化的双层结构预测控制算法及软件实现. 自动化学报, 2014, 40(3):405-414(Pan Hong-Guang, Gao Hai-Nan, Sun Yao, Zhang Ying, Ding Bao-Cang. The algorithm and software implementation for double-layered model predictive control based on multi-priority rank steady-state optimization. Acta Automatica Sinica, 2014, 40(3):405-414)
[14]	李世卿, 丁宝苍, 孙耀. 双层结构预测控制中基于操作变量增量的多优先级稳态目标计算. 控制理论与应用, 2015, 32(2):239-245(Li Shi-Qing, Ding Bao-Cang, Sun Yao. Multi-priority rank steady-state target calculation in double-layered model predictive control by optimizing increments of manipulated variables. Control Theory Applications, 2015, 32(2):239-245)
[15]	曹永岩, 毛维杰, 孙优贤, 冯旭. 现代控制理论的工程应用. 杭州:浙江大学出版社, 2000. (Cao Yong-Yan, Mao Wei-Jie, Sun You-Xian, Feng Xu. Engineering Application of Modern Control Theory. Hangzhou:Zhejiang University Press, 2000.)
[16]	Dayal D S, MacGregor J F. Identification of finite impulse response models:methods and robustness issues. Industrial Engineering Chemistry Research, 1996, 35(11):4078-4090