Modeling, Identification and Control at Telemark University College

Master studies in process automation started in 1989 at what soon became Telemark University College, and the 20 year anniversary marks the start of our own PhD degree in Process, Energy and Automation Engineering. The paper gives an overview of research activities related to control engineering at Department of Electrical Engineering, Information Technology and Cybernetics

Modeling, Identification and Control at Telemark University College

Master studies in process automation started in 1989 at what soon became Telemark University College, and the 20 year anniversary marks the start of our own PhD degree in Process, Energy and Automation Engineering. The paper gives an overview of research activities related to control engineering at Department of Electrical Engineering, Information Technology and Cybernetics

Population balance modelling for fertilizer granulation process

Few granulation plants are operated optimally. It is common to operate granulation plants below their maximum design capacity, and in many cases, periodic instabilities may also occur. From a process control and optimization point of view, it is desirable to develop a dynamic model that can show the dominating dynamics of a granulation process and can be used for design of optimal operation of the granulation plant. In this paper, a dynamic model of a drum granulator is developed using population balance (PB). Different simulation scenarios are used to analyze various granulation mechanisms that are characteristic to drum granulators. Simulation results show that for the drum granulator, the particle agglomeration has a greater impact on the change in particle size distribution (PSD) compared to the particle growth due to layering. In addition, coarser particles are produced when a sizedependent agglomeration kernel is used in the granulator model. For combined processes, i.e., processes where the particle growth due to layering and agglomeration are considered simultaneously, coarser particles with a wider PSD are obtained with the size-dependent agglomeration kernel