An Improved Control Vector Iteration Approach for Nonlinear Dynamic Optimization. II. Problems with Path Constraints

胡云卿; 刘兴高; 薛安克

doi:10.1016/S1004-9541(14)60001-X

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An Improved Control Vector Iteration Approach for Nonlinear Dynamic Optimization. II. Problems with Path Constraints

过程系统工程与过程安全 | Updated：2026-01-06

- An Improved Control Vector Iteration Approach for Nonlinear Dynamic Optimization. II. Problems with Path Constraints
- An Improved Control Vector Iteration Approach for Nonlinear Dynamic Optimization. II. Problems with Path Constraints
- 中国化学工程学报（英文版） 2014年22卷第2期页码：141-1451004-9541
- Affiliations：
  
  2 Institute of Information and Control, Hangzhou Dianzi University,Hangzhou,China,310018
- Author bio：
- Funds：
- DOI：10.1016/S1004-9541(14)60001-X
  中图分类号：
- 纸质出版：2014
- Accepted：
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胡云卿, 刘兴高, 薛安克. An Improved Control Vector Iteration Approach for Nonlinear Dynamic Optimization. II. Problems with Path Constraints[J]. 中国化学工程学报（英文版）, 2014,22(2):141-1451004-9541.

HU Yunqing, LIU Xinggao, XUE Anke. An Improved Control Vector Iteration Approach for Nonlinear Dynamic Optimization. II. Problems with Path Constraints[J]. Chin.J.Chem.Eng., 2014, 22(2): 141-145.
胡云卿, 刘兴高, 薛安克. An Improved Control Vector Iteration Approach for Nonlinear Dynamic Optimization. II. Problems with Path Constraints[J]. 中国化学工程学报（英文版）, 2014,22(2):141-1451004-9541. DOI： 10.1016/S1004-9541(14)60001-X.

HU Yunqing, LIU Xinggao, XUE Anke. An Improved Control Vector Iteration Approach for Nonlinear Dynamic Optimization. II. Problems with Path Constraints[J]. Chin.J.Chem.Eng., 2014, 22(2): 141-145. DOI： 10.1016/S1004-9541(14)60001-X.

摘要

Abstract

This paper considers dealing with path constraints in the framework of the improved control vector iteration (CVI) approach. Two available ways for enforcing equality path constraints are presented

which can be directly incorporated into the improved CVI approach. Inequality path constraints are much more difficult to deal with

even for small scale problems

because the time intervals where the inequality path constraints are active are unknown in advance. To overcome the challenge

the l

penalty function and a novel smoothing technique are introduced

leading to a new effective approach. Moreover

on the basis of the relevant theorems

a numerical algorithm is proposed for nonlinear dynamic optimization problems with inequality path constraints. Results obtained from the classic batch reactor operation problem are in agreement with the literature reports

and the computational efficiency is also high.

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