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This paper deals with the design of a predictive control law for microalgae culture process to regulate the biomass concentration at a chosen setpoint. However, the performances of the Nonlinear Model Predictive Controller usually decrease when the true plant evolution deviates significantly from that predicted by the model. Thus, a robust criterion under model's parameters uncertainties is considered,...
Ground topography under vegetated area is liable to bring significant changes on radar backscattering and thereby on the associated standard retrieval algorithms dedicated to forest biomass. Within the framework of the ESA BIOMASS mission, this paper evinces the evolution of P-band polarimetric intensities with a tilted underlying ground. For that purpose, electromagnetic simulations have been achieved...
The identifiability and estimability properties of dynamical systems have been extensively studied in the literature. However, such approaches often focus on the sensitivity of system trajectories to perturbations in parameter values about some nominal parameter value. Relying on parameter sensitivity to assess parameter estimability can be misleading because the neighbourhood over which the sensitivity...
Sensitivity analysis is a powerful tool which gives important insights regarding parameterization in the process of model design. For an empirical model like the Greenlab model of plant growth relying on parameter estimation from experimental data, such study should open new perspectives for model identification. This study was aimed at analyzing the sensitivity of GreenLab model for maize. When the...
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