The goal of the Automation area is to develop methods for analyzing dynamic systems represented by continuous, discrete or hybrid nonlinear ODEs (Ordinary Differential Equations), PDEs (Partial Differential Equations), FDEs (Fractional Differential Equations), or Markov models, in order to
i) estimate the intrinsic characteristics of their model (estimation of states and parameters),
ii) detect and estimate failures (diagnosis),
iii) evaluate their FMDS performance (Reliability, Maintainability, Availability, Safety),
iv) act on these systems to meet a required objective (control).
Application fields
There are a wide range of application domains, covering disciplines already present in the PRISME laboratory (Signal, IV, Robotics or Esa areas). The Automatic axis specifically targets the following societal challenges:
- Mathematics for health,
- Industry of the future,
- Intelligent energy management.
Themes
The axis has two main themes, in which the members of the axis are equally divided:
- Theme 1 aims to develop observation and control methodologies based on ensemblistic or geometric approaches for different classes of systems.
- Theme 2 aims to develop maintenance strategies using semi-parametric or Markovian approaches, and to design methods for analyzing operating safety.
The two themes share the development of observation tools and certain mathematical analysis tools, notably between sub-themes T1-Observation and control and T2-Maintenance. The study of systems modeled by Markov processes is also common to sub-themes T1-Set methods and T2-Maintenance.
Latest conferences
CDC 2020 Conference: State estimation of the wake flow structures using low power high gain observer and observability singularity avoidance (Javeria AHMED, Matthieu FRUCHARD, Estelle COURTIAL and Youssoufi TOURE)
CDC 2020 Conference: Off-line algorithm for selecting modulating functions & application to PDE (Sharefa ASIRI, Da-Yan LIU, and Taous-Meriem LALEG-KIRATI)
Other videos are availbale on the area’s YouTube Channel.
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