一种高效的快速近似控制向量参数化方法

李国栋; 胡云卿; 刘兴高

doi:10.16383/j.aas.2015.c140031

一种高效的快速近似控制向量参数化方法

doi: 10.16383/j.aas.2015.c140031

1.
浙江大学工业控制技术国家重点实验室杭州 310027;
2.
南车株洲电力机车研究所有限公司株州 412001

基金项目:

国家高技术研究发展计划(863计划)(2006AA05Z226);国家自然科学基金(U1162130);浙江省杰出青年科学基金项目(R4100133)资助

详细信息

作者简介:
李国栋浙江大学控制科学与工程系博士研究生.主要研究方向为过程最优控制.E-mail:liguodong_008@163.com

通讯作者:
刘兴高浙江大学控制科学与工程系教授.主要研究方向为工业过程建模、优化与控制.本文通信作者. E-mail:liuxg@iipc.zju.edu.cn

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- 被引次数: 32
出版历程
- 收稿日期: 2014-01-14
- 修回日期: 2014-05-28
- 刊出日期: 2015-01-20

An Efficient Fast Approximate Control Vector Parameterization Method

1.
State Key Laboratory of Industry Control Technology, Zhejiang University, Hangzhou 310027;
2.
CSR Zhuzhou Institute Co. Ltd., Zhuzhou 412001

Funds:

Supported by National High Technology Research and Development Program of China (863 Program) (2006AA05Z226), National Natural Science Foundation of China (U1162130), and Outstanding Youth Science Foundation of Zhejiang Province (R4 100133)

摘要

摘要: 控制向量参数化(Control vector parameterization, CVP) 方法是目前求解流程工业中最优操作问题的主流数值方法,然而,该方法的主要缺点之一是计算效率较低,这是因为在求解生成的非线性规划(Nonlinear programming, NLP) 问题时,需要随着控制参数的调整,反复不断地求解相关的微分方程组,这也是CVP 方法中最耗时的部分.为了提高CVP 方法的计算效率,本文提出一种新颖的快速近似方法,能够有效减少微分方程组、函数值以及梯度的计算量.最后,两个经典的最优控制问题上的测试结果及与国外成熟的最优控制软件的比较研究表明:本文提出的快速近似CVP 方法在精度和效率上兼有良好的表现.
- 流程工业 /
- 最优控制 /
- 控制向量参数化 /
- 计算效率 /
- 快速近似
Abstract: The control vector parameterization (CVP) method is currently popular for solving optimal control problems in process industries. However, one of its main disadvantages is the low computational efficiency, because the relevant differential equations in solving the generated nonlinear programming (NLP) problem should be calculated repeatedly with the adjustment of control, which is the most time-consuming part of the CVP method. A new fast approximate approach with less computational expenses on differential equations, function values and gradients is therefore proposed to improve the computational efficiency of the CVP method in this paper. The proposed approach is demonstrated to have marked advantages in terms of accuracy and efficiency, in contrast to mature optimal control softwares, on two classic optimal control problems.
- Process industry /
- optimal control /
- control vector parameterization (CVP) /
- computational efficiency /
- fast approximate

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参考文献(25)

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