Non Linear Systems and Process


Scientific expertises:

Automatic, Nonlinear Systems, Observability and Observer Design, Control and Stabilization


The research topic of the SNLEP team concerns the theorical development and implementation of tools devoted to: Analyze, Model, Simulate, Control and Optimize Systems in Process Engineering.

Our theoretical developments are motivated by practical applications encountered through collaborations with industrial and academic partners. More specifically, our work focuses on model design and reduction, parametric identification and observation, diagnosis and control.

  • The Modeling concerns polymerization crystallization freeze and bio- processes. We exploit mainly heat balance and matter conservation law, heat and matter diffusion, mass transfer between phases and population balance in particulate processes to develop models suitable for simulation, observation and control.
  • Identification exploits tools coming from model predictive control and refers to experimental design in order to facilitate online parameter identification.
  • The observation topic refers to the design of algorithm to estimate online parameters and unknown quantities of the model.
  • Fault diagnosis refers to the detection of fault which is an unpermitted deviation of at least one characteristic property of the process from the acceptable, usual, standard condition.
  • The control topic focuses on the stabilization problem for finite and infinite dimensional systems, the tracking and control problem using optimization tools.

The chemical processes mainly concerned by the SNLEP team are polymerization processes, crystallization processes and drying processes.



 Director of SNLEP: Hassan Hammouri


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368 documents

  • Nawel Afsi, Sami Othman, Toufik Bakir, Liborio Costa, Anis Sakly, et al.. Model predictive control for continuous lactide ring‐opening polymerization processes. Asian Journal of Control, Asian Control Association (ACA) and Chinese Automatic Control Society (CACS) 2020, ⟨10.1002/asjc.2453⟩. ⟨hal-02991993⟩
  • O Koçan, Daniele Astolfi, C. Poussot-Vassal, A Manecy. Supervised Output Regulation via Iterative Learning Control for Rejecting Unknown Periodic Disturbances. 21st IFAC World Congress, Jul 2020, Berlin, Germany. ⟨hal-02557323⟩
  • Bertrand Zitte, Boussad Hamroun, Daniele Astolfi, Françoise Couenne. Robust Control of a Class of Bilinear Systems by Forwarding: Application to Counter Current Heat Exchanger. 21st IFAC World Congress, Jul 2020, Berlin, Germany. ⟨hal-02557335⟩
  • Elise Morfin, Daniele Astolfi, Vincent Andrieu. Adaptive low-power high-gain observers for lower-triangular systems with input-dependent Lipschitz constant. 21st IFAC World Congress, Jul 2020, Berlin, Germany. ⟨hal-02557310⟩
  • Vincent Andrieu, Bayu Jayawardhana, Laurent Praly. Characterizations of global transversal exponential stability (long version). 2020. ⟨hal-02851212v2⟩
  • A Terrand-Jeanne, Vincent Andrieu, Valérie dos Santos Martins, C.-Z Xu. Adding integral action for open-loop exponentially stable semigroups and application to boundary control of PDE systems. IEEE Transactions on Automatic Control, Institute of Electrical and Electronics Engineers, 2020, ⟨10.1109/TAC.2019.2957349⟩. ⟨hal-01971584⟩
  • Vincent Andrieu, Daniele Astolfi, Pauline Bernard. Observer design via interconnections of second-order mixed sliding-mode/linear differentiators. International Journal of Robust and Nonlinear Control, Wiley, In press. ⟨hal-02751929⟩
  • Lucas Brivadis, Vincent Andrieu, Ulysse Serres. Luenberger observers for discrete-time nonlinear systems. 2019 IEEE 58th Conference on Decision and Control (CDC), Dec 2019, Nice, France. pp.3435-3440, ⟨10.1109/CDC40024.2019.9029220⟩. ⟨hal-02467958⟩
  • Daniele Astolfi, Giacomo Casadei. Stabilization of nonlinear systems in presence of filtered output via extended high-gain observers. Automatica, Elsevier, 2019, 110, pp.108594. ⟨10.1016/j.automatica.2019.108594⟩. ⟨hal-02319700⟩
  • Bouali Rabaoui, Hamdi Habib, Naceur Benhadjbraiek, Mickael Rodrigues. A reconfigurable PID fault tolerant tracking controller design for LPV systems. ISA Transactions, Elsevier, 2019. ⟨hal-02388923⟩

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