Reliable solution to dynamic optimization problems using integrated residual regularized direct collocation
Author(s)
Nie, Yuanbo
Kerrigan, Eric
Type
Journal Article
Abstract
Direct collocation (DC) is a widely used method for solving dynamic optimization problems (DOPs), but its implementation simplicity and computational efficiency are limited for challenging problems. For DOPs involving singular arcs, DC solutions often exhibit significant fluctuations along the singular arc, accompanied by large residual errors between collocation points, where the dynamic constraints are enforced as equality constraints. In this paper, we introduce the direct transcription method of integrated residual regularized direct collocation (IRRDC). This approach enforces dynamic constraints using a combination of point-wise residual constraints (expressed as either equalities or inequalities) and a penalty term on the integrated residual error, which helps reduce errors between collocation points. IRRDC retains the implementation simplicity of DC while improving both solution accuracy and efficiency, particularly for challenging problem types. Through the examples, we demonstrate that for problems where traditional DC results in excessive fluctuations, IRRDC effectively suppresses fluctuations and yields solutions with greater accuracy — at least two orders of magnitude lower in various error measures in relation to the dynamic and path constraints.
Date Issued
2025-06-18
Date Acceptance
2025-06-02
Citation
IEEE Control Systems Letters, 2025, 9 (1), pp.1063-1068
ISSN
2475-1456
Publisher
Institute of Electrical and Electronics Engineers
Start Page
1063
End Page
1068
Journal / Book Title
IEEE Control Systems Letters
Volume
9
Issue
1
Copyright Statement
© 2025 IEEE. All rights reserved, including rights for text and data mining, and training of artificial intelligence and similar technologies. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.
License URL
Identifier
10.1109/LCSYS.2025.3580771
Subjects
Optimal control
numerical algorithms
predictive control for nonlinear systems
Publication Status
Published
Date Publish Online
2025-06-18