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arXiv Machine Learning By Abdeladhim Tahimi, Rinaldo Vieira da Silva Junior

Dual-Network PINNs for Optimal Control: A Reproducible Benchmark on the Mass-Spring-Damper System

Read the original on arXiv Machine Learning →

arXiv:2606. 15271v1 Announce Type: cross Abstract: This work presents a transparent and reproducible benchmark study of a direct dual-network Physics-Informed Neural Network (PINN) formulation for the optimal control of a mass-spring-damper system.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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