# Jonas-Nicodemus/PINNs-based-MPC

<https://repo.masters-masters.com/en/repos/Jonas-Nicodemus/PINNs-based-MPC>

[Home](https://repo.masters-masters.com/en) › [Jonas-Nicodemus](https://repo.masters-masters.com/en/owners/Jonas-Nicodemus) › [PINNs-based-MPC](https://repo.masters-masters.com/en/repos/Jonas-Nicodemus/PINNs-based-MPC)

Jonas-Nicodemus/PINNs-based-MPC has 156 stars on GitHub. Its RepoMasters card: Prototype tier. We discuss nonlinear model predictive control (NMPC) for…

| Field | Value |
| --- | --- |
| Owner | [Jonas-Nicodemus](https://repo.masters-masters.com/en/owners/Jonas-Nicodemus) |
| Stars | 156 |
| Forks | 32 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2021 |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [Jonas-Nicodemus/PINNs-based-MPC](https://github.com/Jonas-Nicodemus/PINNs-based-MPC) |

## Repository

We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-informed neural networks (PINNs) are a promising tool to approximate (partial) differential equations. PINNs are not suited for control tasks in their original form si…

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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