Model Predictive Control and Parameter Estimation applied to Gene Expression in Yeast

Jody Chochrane (1) , Mazen Alamir (2)

1 UoN - University of Newcastle [Callaghan, Australia]
2 GIPSA-SYSCO - GIPSA - Systèmes non linéaires et complexité

In this paper an adaptive Nonlinear Model Predictive Control (NMPC) scheme is proposed to control the gene expression of yeast using the application of osmostic shocks. The proposed control method handles the presence of delays, input constraints, as well as unknown model parameters during the controlled scenario. A controller was designed that optimized the integer-valued control sequence so that the output trajectory of the system follows a target reference signal. To tackle the unavoidable parameter uncertainties, a dedicated parameter estimation scheme is proposed that is then coupled to the NMPC design. Simulations are presented to assess the efficiency of the proposed framework in addressing the underlying control problem.

Domaines: Automatique / Robotique

Jody Chochrane, Mazen Alamir. Model Predictive Control and Parameter Estimation applied to Gene Expression in Yeast. ROCOND 2018 - 9th IFAC Symposium on Robust Control Design, Sep 2018, Florianopolis, Brazil. ⟨10.1016/j.ifacol.2018.11.123⟩. ⟨hal-02378209⟩