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RealSim

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Reality-Connected Machine Simulation of Heavy Machinery

The RealSim project proposal aims to connect machine simulation to reality in the framework of heavy machinery, which is an interdisciplinary application. The results of this project are expected to optimize machine performance, a... see more

31/08/2026

UIA

227K€

Project Budget: 227K€

Project leader

UNIVERSITETET I AGDER No se ha especificado una descripción o un objeto social para esta compañía.

PARTICIPATION DEPralty Sin fecha límite de participación.

Financing granted El organismo HORIZON EUROPE notifico la concesión del proyecto The day 2023-04-06

HORIZON-MSCA-2022-PF-01-01: MSCA Postdoctoral Fellowships 2022 Expected Outcome:

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characteristics of the participant

Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

Private Information

No hay información privada compartida para este proyecto. Habla con el coordinador.

1 Participantes

UIA

226.75K€ | Leader

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Project duration: 40 months Date Start: 2023-04-06
End date: 2026-08-31

Project leader

UNIVERSITETET I AGDER No se ha especificado una descripción o un objeto social para esta compañía.

Project Budget 227K€

participation deadline Sin fecha límite de participación.

Project description The RealSim project proposal aims to connect machine simulation to reality in the framework of heavy machinery, which is an interdisciplinary application. The results of this project are expected to optimize machine performance, accurately and reliably predict machine failure, and reduce overall development and operation costs, thus, serving the Europe’s priority of green transformation and the United Nation’s sustainable development goal 9. The RealSim project will close the gaps of: (1) Onboard estimations of force and pressure components of heavy machinery; (2) Estimating deformability, cylinder friction, leakage, and valve dynamics of heavy machinery using independent nonlinear Kalman filters; (3) Employing dependent nonlinear Kalman filters in state estimators of heavy machinery; (4) Tuning algorithms for the covariance matrix of plant noise in the state estimation of heavy machinery. I will consolidate and leverage my research career and position as a leading researcher in the field through integration in Assoc. Prof. Mohammad Poursina’s group at the Department of Engineering Sciences of the University of Agder (UiA), Norway. Here, I will acquire hands-on experience of working with actual mechatronic systems and develop efficient control algorithms. I will improve my knowledge of fluid power designing, control theory, instrumentation, and develop efficient coding skills. I will also develop entrepreneurial skills. The skills, knowledge, and international network that I will develop during this fellowship will put me in an excellent position to achieve my long-term goal of becoming a professor with my own independent research group at an esteemed university in EU. This fellowship will help me to prepare a strong ERC Starting Grant application in the future. It will also cater my additional goal of setting-up a research-related start-up in the future.

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