Data-driven Control for Multivariable Systems - Nancy, France - CRAN -CNRS UMR 7039

Description

Data-Driven Control for Multivariable Systems:

• Réf

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ABG-118588

• Sujet de Thèse 01/12/2023
• Contrat doctoral
• CRAN CNRS UMR 7039
• Lieu de travail
• Nancy
• Grand Est
• France
• Intitulé du sujet
• Data-Driven Control for Multivariable Systems
• Champs scientifiques
• Sciences de l'ingénieur

• Mots clés

• Data driven based control, Modelfree control, Vacuum Brazing Furnace
  Description du sujet:

Data-Driven Control for Multivariable Systems

Advisors:

• Pierre Riedinger
• Jamal Daafouz
  Context and motivation:
• In the rapidly evolving landscape of artificial intelligence (AI), the integration of data-driven control strategies represents a paradigm shift in enhancing system performance and adaptability. The growing interest in data-driven control is motivated by their ability to bypass explicit identification steps, a significant time sink in traditional control design [1, 2, 3]. This approach enables the utilization of data to directly achieve the desired control design objectives. Nevertheless, particularly in the realm of complex systems, the adoption of data-driven design strategies remains unconsolidated. This is attributed to the absence of guarantees and a comprehensive understanding of the closed-loop behavior before deploying the controller. Moreover, the increasing complexity of modern engineering systems, particularly those with multiple interacting variables, poses significant challenges. Multivariable systems exhibit intricate dynamics necessitating innovative strategies for effective control. This research aims to explore and develop advanced data-driven techniques to enhance the control performance of multivariable systems.-
  Methodology:
• Conduct a comprehensive review of existing literature on data-driven control and multivariable systems.
• Design and implement datadriven control algorithms, considering the challenges posed by considering multiple inputs and multiple outputs systems.
• Evaluate the performance of the proposed algorithms through extensive simulations and validate the results with experimental data if possible.
• Compare the proposed datadriven control strategies with traditional control methods, highlighting the advantages and limitations of each approach

Prise de fonction:

• 01/09/2024
  Nature du financement:
• Contrat doctoral

Précisions sur le financement:

• BPI France 2030
  Présentation établissement et labo d'accueil:
• CRAN CNRS UMR 7039

Created in 1980, the "Centre de Recherche en Automatique de Nancy (CRAN)" is a joint research unit (UMR 7039) shared by the University of Lorraine (UL) and the CNRS "Institut des sciences de l'information et de leurs interactions (INS2I)".It also hosts researchers from the "Lorraine Cancer Institute" (ICL, Centre de lutte contre le cancer), the University Hospital., the Regional Hospital Center of Metz-Thionville and the LIST in Luxembourg-City.

As of January 1, 2022, the laboratory has 106 professor-researchers, 4 emeritus, 9 CNRS researchers, 9 other researchers from UL, ICL and CHU or external organizations, 13 post-doctoral fellows, 90 doctoral students and 34 (including 29 permanent and 5 fixed-term contracts) engineers, technicians or administrators.

It is part of the Charles Hermite Automatique, Informatique, Mathématiques de Lorraine Research Federation and the Automatique, Mathématiques, Informatique et leurs Interactions (AM2I) scientific pole of the University of Lorraine.

Based on digital sciences, the laboratory is internationally recognized for its activities in the fields of signal and image processing, control and computer engineering, as well as for its work in health in connection with biology and neuroscience.

Today, its fundamental and applied research enables it to accompany the changes in society and goes beyond the traditional industrial issues:
energy production, management of the intelligent city or transport. In health, it is opening up to diagnosis and care in cancerology and neurology.

They are crossing sociology, listening to social behaviors and opinion dynamics, and investing in the field of sustainable development, in the service of the circular economy and ecological systems.

Site web:


Intitulé du doctorat:

• Doctorat Automatique et traitement du signal
  Pays d'obtention du doctorat:
• France

Etablissement délivrant le doctorat:

• Université de Lorraine
  Ecole doctorale:
• Informatique
• Automatique Électronique Électrotechnique
• Mathématiques de Lorraine (IAEM-Lorra
• You are a talented and enthusiastic young researcher.
• You have experience or knowledge in the field of dynamic systems and control.
• You have preferably completed studies in systems and control, mechanical or electrical engineering, or (applied) mathematics.
• You work well in a team and are interested in methodological research.
• You have good communication skills and a cooperative attitude to working in a research team.
• You are creative and amb