Showing papers by "Hassan Hammouri published in 2007"

Uniform observability and observer synthesis

Abstract: The single input observability is the practical observability notion that can be used for the state and parameter estimation. A system is single input observable if there exists an input which distinguishes any different initial states (see chapter 1). Such inputs are called universal inputs. For analytic systems the observability is equivalent to the single input observability (see [19]). For nonlinear systems, even if the system is single input observable, it may admit an input which renders it unobservable. However, for stationary linear systems, the single observability doesn’t depend on the input and can be characterized using a Brunowsky canonical form [21]. The property that the single input observability doesn’t depend on the input will be called the uniform observability. As for stationary linear systems, canonical forms can be designed in order to characterize some class of uniformly observable nonlinear systems.

Optimization and control of the freeze-drying process of pharmaceutical products

Abstract: A system is described for monitoring the lyophilisation process of a product in containers (4, 4a, 4b) arranged inside a lyophilisation chamber, comprising a temperature measurement system (6) associated with each container housed inside (10) said lyophilisation chamber, capable of surveying local temperature data for each container. The system includes: a wireless communication system (8) for the surveyed temperature data; and a processing module (16) for said data, located externally to the lyophilisation chamber, programmed to determine at least one parameter indicative of the progress of the lyophilisation process not measured by the measurement system, by means of a predetermined representation model of the process, capable of correlating a local temperature value of the container with said parameter.

Model predictive control of the primary drying stage of the drying of solutions in vials: an Application of the MPC@CB Software (Part 1)

Abstract: This paper deals with the first principle model based predictive control of the primary drying stage of a freeze drying of solutions in vials. In the proposed control approach, any online control problem concerned with a constrained optimization during the primary drying stage may be stated. It is solved using a special model predictive control framework where the model is used in the controller formulation. Our first simulation results show here the efficiency of the control software developed (MPC@CB) under Matlab. MPC@CB may be easily used for any other process and any constrained control problem.

Destruction of volatile organic compounds by the optimal multivariable control of a catalytic reverse flow reactor

Abstract: This paper aims to compare 2 optimal control laws for a catalytic reverse flow reactor (RFR), which topic has not often been tackled. The RFR aims to destruct volatile organic compounds (VOCs), which are noxious products and are the source of a lot of problems: pollution, acid rains, woods wasting, green house effect and health hazards. Due to the public regulations, the VOCs discharge in the atmosphere becomes therefore more and more limited. The RFR is characterized by a periodic cycle of treatment of the VOC flow, allowing trapping the heat of reaction inside the core of the RFR. This allows using the RFR in an autothermal mode. The control problem tackled here is to maintain the RFR is this mode, such that the RFR extinction is avoided, and such that the catalyst elements are not destroyed. Effects of the influencing stochastic variations of the inlet pollutant concentration (the input disturbance) have to be accounted for by the optimal constrained tuning of the dilution rate and the internal electric heating. Optimal closed-loop performances of a linear quadratic regulator (LQR) and a model predictive controller (MPC) are compared through simulations.