Levente L. Simon

Swelling Constrained Control of an Industrial Batch Reactor Using a Dedicated NMPC Environment: OptCon

This work presents the application of nonlinear model predictive control (NMPC) to a simulated industrial batch reactor subject to safety constraint due to reactor level swelling. The reactions are equilibrium limited, one of the products is in vapor phase, and the catalyst decomposes in the reactor. The catalyst is fed in discrete time steps during the batch, and the end-point objective is the maximum conversion in a fixed time. The reaction kinetics is determined by the temperature profile and catalyst shots, while the chemical equilibrium is shifted by operating at low pressure and removing one of the products. However, the formed vapor causes liquid swelling, due to the gas or vapor stream resulted from the reaction. As a result reaction mass may enter in the pipes and condenser, creating productivity losses and safety hazard. The end-point objective function (maximum conversion) of this problem can be converted into a level set point tracking problem. The control method is based on the moving horizon NMPC methodology and a detailed first-principles model of reaction kinetics and fluid hydrodynamics is used in the controller. The NMPC approach is based on the sequential quadratic programming (SQP) algorithm implemented in a user-friendly software environment, OptCon. The application of the fast real-time iteration scheme in the NMPC allows the use of small sampling period minimizing this way the violation of the maximum level constraints, due to disturbances within sampling period.

Modeling of a Three-Phase Industrial Batch Reactor Using a Hybrid First-Principles Neural-Network Model

We present an industrial case study of a three-phase reaction system in a batch reactor. For the successful modeling and prediction of the plant-scale performance, a hybrid model is used. Data from different scales were available for developing and testing the model. Laboratory data from a 1 kg vessel were used for the determination of the parameters related to reaction kinetics. Here, a first-principle approach is applied for modeling reactions and dissolution of one reactant that is introduced into the reactor in solid form. To model the large-scale production process, this model was extended with neural-network models to identify the missing parameters. In addition, a refitting of the kinetic parameters on the plant scale was required. With this hybrid model, a good prediction of the concentration courses in the industrial reactor was obtained and improved operating conditions were identified. This paper discusses the potentials and limitations of applying hybrid models in complex processes in the chem...

Real time Takagi-Sugeno fuzzy model based pattern recognition in the batch chemical industry

This contribution describes the real time pressure check pattern recognition of an industrial batch dryer. The goal is to identify the start of the drying process and to calculate the time elapsed between two consequent batch starts (batch time) right after the batch has completed. The presented pattern recognition method implements a supervised learning approach based on Takagi-Sugeno fuzzy (TS) models. The decision maker design is based on plant data compressed by the PI algorithm (OSI Software, Inc). It is concluded that the developed classifier is able to perform real time classification and the compressed PI data can be used in order to design data analysis tools which are useful for chemical batch plant operation investigations.

Bulk Video Imaging for Nucleation Detection and Metastable Zone Determination of Pharmaceutical and Food Crystallization Processes

Abstract This work presents the comparison of bulk video imaging (BVI) approach with the focused beam reflectance measurement (FBRM) and ultra violet/visible spectroscopy. The BVI concept is presented on the caffeine and palm oil crystallization processes and it is shown that BVI is able to detect the nucleation onset with performance comparable to the other two sensors.

Nonlinear model predictive control of an industrial batch reactor subject to swelling constraint

This paper presents the application of nonlinear model predictive control (NMPC) to a simulated industrial batch reactor subject to safety and productivity constraints due to swelling. The catalyst used in the chemical process decomposes in the reactor; therefore it is fed in discrete time steps during the batch. Although the optimal reactor temperature profile, using a fixed catalyst dosing policy, is optimized off-line an on-line control solution is needed in order to accommodate the reaction rate and level disturbances which arise due to catalyst dosing uncertainty (feeding time and mass). The on-line control method is based on the shrinking horizon optimal control methodology and it uses a reaction and hydrodynamic model. It is concluded that the implemented shrinking horizon on-line optimization strategy is able to calculate the optimal temperature profile without causing level swelling.

Knowledge on asthma, food allergies, and anaphylaxis: Assessment of elementary school teachers, parents/caregivers of asthmatic children, and university students in Uruguaiana, in the state of Rio Grande do Sul, Brazil

INTRODUCTION Allergic diseases have become an increasingly common reality in the last years, extending beyond the family context. OBJECTIVE Assessing the level of knowledge on asthma, food allergies and anaphylaxis of asthmatic childrens parents/caregivers (PC), elementary school teachers (EST) and university students (US) in Uruguaiana, RS, Brazil. METHOD 577 individuals (PC - N=111; EST - N=177; US - N=299) took part in the study, answering the Newcastle Asthma Knowledge Questionnaire (validated for Portuguese) and another questionnaire on Food Allergy (FA) and anaphylaxis. RESULTS Although PC have asthmatic children, their asthma knowledge level was average, slightly above that of EST and EU. The lack of knowledge on passive smoking, use of medications and their side effects should be highlighted. US have shown to be better informed about FA and anaphylaxis. However, even though a significant proportion of respondents know the most common symptoms of FA and anaphylaxis, few named subcutaneous adrenaline as the drug of choice for treating anaphylaxis. Although a significant number of respondents know about the possibility of anaphylactic reactions happening at school or in activities outside the school, we were surprised by the absence of conditions in schools to provide emergency care to such students. CONCLUSION Despite the high prevalence of allergic diseases in childhood, asthmatic childrens parents/caregivers, elementary school teachers and university students have inadequate levels of knowledge to monitor these patients.

On-line model based control of a safety constrained batch reactor subject to recipe uncertainties

This contribution presents the on-line model based level control of a batch reactor with reaction rate uncertainties. The analyzed chemical batch process is catalyzed by a catalyst which decomposes in the reactor; therefore it is fed several times during the batch. Although the optimal reactor temperature profile, using a fixed catalyst dosing policy, is optimized off-line an on-line control solution is needed in order to accommodate the reaction rate and level disturbances which arise due to catalyst dosing uncertainty (feeding time, mass and purity). The chemical reaction produces a vapour phase by product which causes the level change of the reaction mixture. The on-line control method is based on the shrinking horizon optimal control methodology and it uses a reaction and hydrodynamic model. It is concluded that the on-line level control strategy delivers good level control results despite the disturbances and an output feedback controller is needed to control the level on a discretization interval.

Nonlinear model predictive control of a swelling constrained industrial batch reactor

Abstract This paper presents an on-line model based level control of a batch reactor with reaction rate uncertainties. The analyzed chemical batch process is catalyzed by a catalyst which decomposes in the reactor; therefore it is fed several times during the batch. The chemical reaction produces a vapour phase by-product which causes level change in the system. The on-line control method is based on the shrinking horizon optimal control methodology based on the detailed model of the process. The results demonstrate that the on-line optimization based control strategy provides good control performance despite the disturbances.

Optimal temperature control of an industrial batch reactor with regard to swelling

Abstract The contribution of this work deals with the optimization of the temperature profile of a three-phase batch reaction with regard to swelling phenomena. The optimization procedure is carried out in the form of an optimal control problem. The system is modeled using a dynamic first-principles model for the reaction which is linked to a hydrodynamic model.