Modeling System Dynamics with Physics-Informed Neural Networks Based on Lagrangian Mechanics

29 May 2020 • Manuel A. Roehrl • Thomas A. Runkler • Veronika Brandtstetter • Michel Tokic • Stefan Obermayer

Identifying accurate dynamic models is required for the simulation and control of various technical systems. In many important real-world applications, however, the two main modeling approaches often fail to meet requirements: first principles methods suffer from high bias, whereas data-driven modeling tends to have high variance... (read more)

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