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Advanced process control can benefit to the operation efficiency and quality of tablets produced by wet granulation lines. Following the development of a new fully continuous fluidized bed reactor as a potential substitute for the current batch dryer design, this paper examines the energy and product quality performances of two predictive control strategies using an experimentally validated simulator. The first one proposes an economic model predictive controller explicitly minimizing the dryer energy consumption. The second one follows the same objective, but uses a simpler classical predictive control framework implementing targets on manipulated variables to drive them toward low energy consumption operating points. Both controllers lead to similar performances, and consume about 20% less energy than a reference feedback scheme without manipulated variable setpoints. Results also show that tracking the product quality attribute significantly benefits from a feedforward action because of the long residence time. This article addresses a subject little explored by the literature, the control of continuous fluidized bed dryers, and clearly demonstrates that a standard linear strategy can reduce the operating costs with an appropriate design. • Predictive control is applied on a simulated continuous fluidized bed dryer. • An economic model predictive controller (EMPC) minimizes the energy consumption. • A more standard predictive controller (MPC) also aims for low-energy actions. • Both EMPC and MPC results in low-energy operations. • Feedforward compensation improves the product quality in both cases. [ABSTRACT FROM AUTHOR]

The availability of reliable online moisture content measurements exploiting near-infrared (NIR) spectroscopy and chemometric tools allows the application of online control strategies to a wide range of drying processes in the pharmaceutical industry. In this paper, drying of particles with a pilot-scale batch fluidized bed dryer (FBD) is studied using a in-line NIR probe. A consolidated phenomenological state-space model of an FBD based on mass and energy balances is calibrated applying a nonlinear least-square identification to experimental data (grey-box modeling). Then, relying on the calibrated model, a nonlinear model predictive controller and a moving horizon state estimator are designed. The objective is to reach a specific particle moisture content setpoint at the end of the drying batch while decreasing cycle time and limiting particle temperature. A penalty term on the energy consumption can also be added to the usual tracking control cost function. Compared to a typical FBD operation in industry (mostly open-loop), it is shown that the drying time and the energy consumption can be efficiently managed on the pilot-scale process while limiting various operation problems like under drying, over drying, or particles overheating. [ABSTRACT FROM AUTHOR]

The cooling zone of an induration furnace exhibits a nonlinear dynamic behavior in addition to a strong coupling between output pressure and temperature. Simulation studies show that linear controller performance is unacceptable from an industrial point of view. In order to obtain adequate performance on a wide operating range, a nonlinear predictive controller (NLMPC) based on a phenomenological process model is proposed. Since the furnace simulation model shows that the equipment behaves as a Hammerstein model, a variable change is performed and a linear model predictive controller (MPC) is developed for the cooling zone. Both controllers are tested for set-point changes and disturbance rejection and give relatively similar performances. It is concluded that for processes having structured nonlinearities, as the cooling zone considered here, linear MPC should be preferred to NLMPC since the computation time is far less demanding and the industrial implementation easier. [ABSTRACT FROM AUTHOR]

• A dynamic model of a continuous horizontal fluidized bed dryer is developed. • A screw conveyor control the product residence time in the dryer. • The model allows for gas bubbles and product axial mixing. • Parameters are lumped and equations are solved at low computational costs. • Simulation results are consistent with theory. The bottleneck of pharmaceutical continuous wet granulation lines may often be the drying stage. The introduction of horizontal fluidized beds is currently contemplated to solve this issue, inter alia. However, it would require an appropriate process control system to reach and maintain over time the targeted residual moisture of the product. To support the endeavor of both the process and control designs, this paper develops a dynamic model with lumped parameters of a continuous horizontal fluidized bed dryer equipped with a screw conveyor. To this end, the framework makes use of a two-phase tanks-in-series configuration, thus taking into account expected gas bypasses (bubbles) and product axial mixing. Array programming and vectorized operations on each tank reactor allow solving equations explicitly at a low computational cost. Simulation results for calcium carbonate granules in a laboratory scale dryer are consistent with fluidization, drying and continuous reactor fundamentals. [ABSTRACT FROM AUTHOR]