Adrie E. M. Huesman

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This article presents an output feedback nonlinear model-based control approach for optimal operation of industrial batch crystallizers. A full population balance model is utilized as the cornerstone of the control approach. The modeling framework allows us to describe the dynamics of a wide range of industrial batch crystallizers. In addition, it(More)
This article presents a model-based control approach for optimal operation of a seeded fed-batch evaporative crystallizer. Various direct optimization strategies, namely, single shooting, multiple shooting, and simultaneous strategies, are used to examine real-time implementation of the control approach on a semi-industrial crystallizer. The dynamic(More)
An on-line optimization strategy is developed and applied to a semi-industrial crystallization process. The seeded fed-batch crystallizer is represented by a nonlinear moment model. An optimal control problem pertinent to maximization of the batch crystal yield is solved using the sequential optimization approach. As the dynamic optimizer requires knowledge(More)
This paper presents a model-based control and optimization approach for real-time improved operation of industrial batch crystallization processes. The control approach is successfully tested on a pilot as well as on a full-scale industrial crystallizer. The core component of the control approach is a nonlinear model predictive controller or a nonlinear(More)
A substantial amount of materials in the pharmaceutical, food, and fine chemical industry is produced in crystalline form. Batch crystallization is a key separation and purification unit in such industries, with a significant impact on the efficiency and profitability of the overall process. Advanced model-based control of crystallization processes offers(More)
This study investigates the effectiveness of various nonlinear estimation techniques for output feedback model-based control of batch crystallization processes. Several nonlinear observers developed under deterministic and Bayesian estimation frameworks are applied for closed-loop control of a semi-industrial fed-batch crystallizer. The performance(More)
In this paper, the focus will be on approximating original model of process systems using block-structured models. The context of model reduction is to improve the computational efficiency (simulation time). The reduced order models are important for online applications. Hammerstein structures have been used to approximate a mathematical non-linear model of(More)
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