The short term optimization and control of district heating networks is of great interest for Energy Industries because of the technical, economical and environmental benefits which could be earned from an appropriate management. However, models of such complicated systems are strongly non linear and suffer from important uncertainties. In this article, models well suited to industrial issues are first designed. The whole technological string "production -distributionconsumption" is taken into account. The aim of this study is then to compute an optimal and robust control law for the network. Because of the errors in consumers' demand prediction and modelling uncertainties, a closed loop strategy has to be used to compute a robust control law for the district heating network. In this paper, a robust predictive control strategy of the network is thus developed. The method has been successfully tested on a benchmark network created by EDF ('Electricite de France') and some results are presented here.

In the framework of environment preservation, microalgae biotechnology appears as a promising alternative for CO₂ mitigation. Advanced control strategies can be further developed to maximize biomass productivity, by maintaining these microorganisms in bioreactors at optimal operating conditions. This article proposes the implementation of Nonlinear Predictive Control combined with an on-line estimation of the biomass concentration, using dissolved carbon dioxide concentration measurements. First, optimal culture conditions are determined so that biomass productivity is maximized. To cope with the lack of on-line biomass concentration measurements, an interval observer for biomass concentration estimation is built and described. This estimator provides a stable accurate interval for the state trajectory and is further included in a nonlinear model predictive control framework that regulates the biomass concentration at its optimal value. The proposed methodology is applied to cultures of the microalgae Chlorella vulgaris in a laboratory-scale continuous photobioreactor. Performance and robustness of the proposed control strategy are assessed through experimental results.

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This paper proposes a novel strategy for completing a flight plan with a quadrotor UAV, in the context of aerial video making. The flight plan includes different types of waypoints to join, while respecting flight corridors and bounds on the derivatives of the position of the quadrotor. To this aim, non-uniform clamped B-splines are used to parameterize the trajectory. The latter is computed in order to minimize its overall duration, while ensuring the validation of the waypoints, satisfying the flight corridors and respecting the maximum magnitude on its derivatives. A receding waypoint horizon is used in order to split the optimization problem into smaller ones, which reduces the computation load when generating pieces of trajectories. The effectiveness of the proposed trajectory generation technique is demonstrated by simulation and through an outdoor flight experiment on a quadrotor.