G. Casamatta

Application of iterative learning control to an exothermic semibatch chemical reactor

Focuses on the temperature control of a semibatch chemical reactor used for fine chemicals production. Such a reactor is equipped with a heating/cooling system composed of different thermal fluids. Without extensive modeling investigations, a feedback-feedforward control strategy is proposed for ensuring the tracking performance of the desired temperature profile. Such a strategy is derived from a family of the iterative learning control (ILC) algorithms named batch model predictive control (BMPC). Learning is achieved without requiring a detailed knowledge of the system, which may be affected by unknown but repetitive disturbances. The learning control solution is based on the minimization of a linear quadratic cost function. The synthesis of the proposed strategy is studied, and improvements of the algorithm features are proposed. First, guaranteed convergence of the algorithm is illustrated in a few experimental runs. Second, some practical considerations for the removal of high-frequency disturbance effects are outlined to improve the achieved performance. Third, a robust supervisory control procedure is employed to choose the right fluid and to reduce the superfluous fluid changeovers, mainly when different fluids are available. Finally, experimental results are presented to illustrate the practical appeal and effectiveness of the proposed scheme.

Influence of mass transfer direction on the operation of a pulsed sieve-plate pilot column

Abstract Experimental work has been carried out in order to determine the influence of mass transfer direction on the operation of a pilot pulsed sieve-plate column. The liquid system involved was the water—acetone—toluene, as recommended by the E.F.C.E. Experimental results (hold-up, drop size distributions) have been compared with the predictions of a drop population balance model, which is based on transport, breakage and coalescence laws. It is assumed that transport is weakly sensitive to mass transfer and mass transfer direction. Additional experiments have provided the laws for breakage, exhibiting the influence of mass transfer. Coalescence has been assumed to be negligible with C→D mass transfer direction, and a collision model has been used for D→C mass transfer direction. The resulting drop population model predictions are in fairly good agreement with the experimental data. From a practical point of view, the efficiency in the case of D→C mass transfer direction revealed itself to be higher than in the opposite direction, in spite of a lower interfacial area.

Dynamic and steady-state simulation of hydrodynamics and mass transfer in liquid—liquid extraction column

Abstract The present paper deals with the simulation of the disperesed phase behaviour in liquid—liquid extraction column by means of a drop population balance model. This model takes explicity into account drop transport, break-up, coalescence and mass transfer mechanisms to which the drops are subject. The discrete model is a non-linear, large, sparse and stiff system of coupled differential equations. Various algorithms convenient to the numerical conditions were used for the resolution of the model either dynamically (start-up, perturbation) or at steady-state regime. By simulation, the influence of the different basic mechanisms involved have been clearly exhibited. In addition, the optimal working conditions of extraction columns have been discussed. It was also possible to check the efficiency of the different algorithms that have been developed.

Adaptive control of a multipurpose and flexible semi-batch pilot plant reactor

Abstract Semi-batch operation is currently used in the pharmaceutical or fine chemical industry. Control of such an operation is difficult to ensure by conventional PID as operating conditions and operations change a lot even for the same apparatus. So it is very important in the fine chemical industry to maintain the flexible and multipurpose characters of batch reactors during their automation. This study deals with adaptive thermal control of different kinds of operation (heating, cooling, exothermic reactions carried out in a semi-batch jacketed pilot reactor. Experimental results show the robustness of the algorithm in respect to strong disturbances, its ability of tracking high nonlinear setpoint trajectories and its good control qualities during various chemical reactions.

Gas-liquid-liquid reaction using water soluble catalyst

Abstract Industrial applications of homogeneous catalysis by precious metal complexes are limited due to the difficult recovery or regeneration of such catalysts. By using water soluble phosphorous ligands, the catalytic complex can be kept in aqueous phase. The major drawback, a drastic reduction of the effective reaction rate, has been overcome by adding a cosolvent. Water-octene-cosolvent equilibrium has been estimated (UNIFAC) in order to select a convenient cosolvent, i.e. increasing significantly the octene concentration in the aqueous phase without losing catalyst in the organic phase. Similar thermodynamic prediction of liquid-gas equilibria has then been performed, showing only moderate effects of the cosolvent. Due to ligands oxidation by water, catalyst stability must be improved by increasing the concentration of phosphorous ligands. Then initial kinetics, derived without any mass transfer limitations, showed first order reaction rates with respect to hydrogen and octene-1 in the aqueous phase. Complete kinetics of parallel hydrogenation and isometrisation have been analysed, using step by step liquid-liquid and liquid-gas equilibria accounting for octene consumption.

Simulation of a pneumatically pulsed liquid-liquid extraction column

Abstract The model presented simulates the hydrodynamic operation of a pneumatically pulsed countercurrent liquid-liquid extraction column. A balance on the droplet population is compiled at all levels of the column. This balance, which accounts for transport, rupture and coalescence mechan The experimental results obtained in steady-state conditions on a pilot plant facility served to validate the proposed model. Dynamic simulations of va

Use of neural networks for liquid-liquid extraction column modelling: an experimental study

Abstract This paper presents a new application of neural networks to the modelling of a chemical pilot plant: a pulsed liquid–liquid extraction column. This separation process presents a highly non-linear behaviour and time-varying dynamics. Usually, physical simulation models of chemical plants describing some aspects of hydrodynamics and mass transfer are static or very complex and need excessive computer time. It is proposed that improved predictions can be obtained using a multilayer artificial neural network instead of the physical model of the process. The results obtained illustrate the successful application of such a neural network modelling approach.

Adaptive Model Predictive Control

This paper gives an overview of our studies on adaptive control performed in our laboratory for more than ten years enlightened by results of practical applications on different pilot plants. Applications have been made in two fields: continuous processes such as liquid-liquid extraction columns and batch processes, typically batch or semibatch reactors. Formerly a classical adaptive controller based on a “black-box” model: the Generalized Predictive Controller with Model Reference (GPCMR) has been used. Results were very good in the case of continuous processes but showed the limits of this type of algorithm when applied to batch processes with large changes of dynamics and long time delay. So, a special part is devoted to focus on the important advantages and improvements brought by the use of an Adaptive Model-based Controller in comparison with the classical GPCMR.

Realistic model-based predictive and adaptive control of batch reactor

Abstract This paper presents an original approach which makes use of a realistic thermal model for adaptive predictive control and supervision of a semibatch jacketed reactor. The first part is devoted to the development of an adaptive controller based on a reaUstic model established by thermal balances on the reactor and its jacket. As a first interest, an on-line deterministic estimator of the heat generated during the reaction is developed. In a second part a realistic model is used for model supported supervision to prevent temperature overshoot, especially in the case of industrial reactors, the temperature control being ensured by the adaptive controller.

Experimental application of nonlinear model predictive control: temperature control of an industrial semi-batch pilot-plant reactor

This paper describes the application of nonlinear model predictive control (NMPC) to the temperature control of a semi-batch chemical reactor equipped with a multi-fluid heating/cooling system. The strategy of the nonlinear control system is based on a constrained optimisation problem, which is solved repeatedly on-line by a step-wise integration of a nonlinear dynamic model and optimisation strategy. A supervisory control routine has been developed, based on the same nonlinear dynamic model, to handle automatically the fluid changeovers. Both NMPCand supervisory control have been implemented on a PCand applied to a 16 l batch reactor pilot plant. Experiments illustrate the feasibility of such a procedure involving predictive control and supervisory control. # 2002 Elsevier Science Ltd. All rights reserved.