Slack variable-based control variable parameterization method for constrained engineering optimization

In this paper, a slack variable-based control variable parameterization (CVP) method is proposed for solving engineering dynamic optimization problems with inequality path constraints. An improved slack variable transform technique is introduced so that the original problem is converted into an unco...

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Published in:2017 Chinese Automation Congress (CAC) pp. 6800 - 6805
Main Authors: Ping Liu, Guodong Li
Format: Conference Proceeding
Language:English
Published: IEEE 01.10.2017
Subjects:
Differential equations
dynamic optimization
Dynamic programming
inequality path constraints
Mathematical model
Optimization
Performance analysis
slack variable method
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Abstract In this paper, a slack variable-based control variable parameterization (CVP) method is proposed for solving engineering dynamic optimization problems with inequality path constraints. An improved slack variable transform technique is introduced so that the original problem is converted into an unconstrained dynamic optimization problem (uDOP). No approximation error generated and the inequality path constraints are satisfied during the whole time intervals. A nonlinear programming (NLP) problem, which approximates the original dynamic optimization problem, is obtained by applying the control variable parameterization. The variational method is derived to calculate the gradients so that the transformed NLP problem can be easily solved. Test results show that the proposed method performs better than the penalty method in terms of computation accuracy and computation time.
AbstractList In this paper, a slack variable-based control variable parameterization (CVP) method is proposed for solving engineering dynamic optimization problems with inequality path constraints. An improved slack variable transform technique is introduced so that the original problem is converted into an unconstrained dynamic optimization problem (uDOP). No approximation error generated and the inequality path constraints are satisfied during the whole time intervals. A nonlinear programming (NLP) problem, which approximates the original dynamic optimization problem, is obtained by applying the control variable parameterization. The variational method is derived to calculate the gradients so that the transformed NLP problem can be easily solved. Test results show that the proposed method performs better than the penalty method in terms of computation accuracy and computation time.
Author Ping Liu
Guodong Li
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  surname: Guodong Li
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  email: liguodong_008@163.com
  organization: China Acad. of Electron. & Inf. Technol. Beijing, Beijing, China
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Snippet In this paper, a slack variable-based control variable parameterization (CVP) method is proposed for solving engineering dynamic optimization problems with...
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StartPage 6800
SubjectTerms Differential equations
dynamic optimization
Dynamic programming
inequality path constraints
Mathematical model
Optimization
Performance analysis
slack variable method
Transforms
Title Slack variable-based control variable parameterization method for constrained engineering optimization
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