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An adjoint-oriented Meta-Auto-Decode method for solving Parameterized Optimal Control Problems

delete2025-12-26
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PRE
AI
J
Jinjun Yong
X
Xianbing Luo
S
Shuyu Sun
C
Changlun Ye
DOI：10.1016/j.cnsns.2025.109619delete
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Abstract

Abstract

En 中文
• A novel Adjoint-Oriented Meta-Auto-Decoder (AOMAD) method is designed for solving parameterized optimal control problems • A multi-scale neural network framework is constructed to implement the AOMAD algorithm for two different fine-tuning modes of the AOMAD method • The effectiveness of using the AOMAD method in solving POCPs is demonstrated by three different numerical examples

Journal

Communications in Nonlinear Science and Numerical Simulation cover
Communications in Nonlinear Science and Numerical Simulation
IF:
3.8
Papers:
9.1K
Citations:
1.8W

Organization

T
tongji university
Scholars:
7.7W
Papers: 5.9W
Citations: 98
G
guizhou university
Scholars:
2.4W
Papers: 1.3W
Citations: 15
G
guizhou normal university
Scholars:
4.6K
Papers: 2.4K
Citations: 4
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