CE10 - Usine du futur : Homme, organisation, technologies

Automation and supervision of intensified processes – ASPI

Submission summary

The ASPI project is mainly motivated by the development of an added value system engineering concerning the control problem of intensified chemical processes. These issues range from the control system design to its supervision with a particular emphasis on those fundamental functions regarding the diagnosis, the prognosis as well as predictive maintenance. Supervision will be elaborated from the best available results on fault diagnosis and identification, observer’s synthesis, system identification, faults tolerant control and efficient procedures for signal processing. These methodologies will allow man to be unloaded from a part of the process monitoring while increasing the operational safety. For this, it will be necessary to anticipate and correct any drifts or dysfunctions that could lead to accidental situations.
These techniques will be applied to an industrial field that is particularly critical from the point of view of safety and the catastrophic consequences that accidents can cause: chemistry and more specifically fine chemistry, pharmaceutical chemistry and new syntheses for the valorization of biomass. Another aspect of the project concerns the transformation of production processes through the implementation of innovative processes in the field of process intensification that prefigure the chemical plant of the future. In the production line, the reactor occupies a central place because chemical reactions occur in it. Reactions are highly non-linear operations with respect to the different operating conditions and whose control is crucial in relation to productivity and safety. In the project, we will focus more specifically on new types of multifunctional, continuous reactors that are an alternative to traditional 'batch' reactors. These intensified reactors radically improve the transport and transfer properties (thermal and mass) and allow implementing reactions by approaching the intrinsic limits of their kinetics.
This interdisciplinary fundamental and methodological research work will be performed in collaboration between laboratories of Chemiacl Engineering and Automatic: LGC, LAAS, LAC and LSPC. Fundamentally, this involves the development of experimental modeling, observer synthesis, identification and error detection and fault-tolerant control approaches for intensified reactors. These approaches will be particularly used to develop a control system with a predictive ability to anticipate accidental situations.
From chemical engineering point of view, the control system must guarantee the operational safety of the intensified processes. Particular attention will be paid to the development of a realistic simulator of static and dynamic behaviors and the creation of a fault database for the supervision of the control system and its reconfiguration if necessary. This requires good modeling of reactors in degraded mode with management of model changes in case of fault detection.
Experimental validations will be carried out on pilots available in laboratories to highlight the added value of the developed approaches. Two situations will be addressed: an implementation in a case already studied both from the point of view of the apparatus and the chemical system and the generalization to a system (reactor and chemical synthesis) for which the characterization is still incomplete.

Project coordinator

Monsieur Michel CABASSUD (LABORATOIRE DE GENIE CHIMIQUE)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

LGC LABORATOIRE DE GENIE CHIMIQUE
LAAS-CNRS Laboratoire d'Analyse et d'Architecture des Systèmes
LSPC LABORATOIRE DE SECURITE DES PROCEDES CHIMIQUES
LAC Laboratoire d'Automatique de Caen

Help of the ANR 496,800 euros
Beginning and duration of the scientific project: March 2020 - 48 Months

Useful links

Explorez notre base de projets financés

 

 

ANR makes available its datasets on funded projects, click here to find more.

Sign up for the latest news:
Subscribe to our newsletter