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Christer Haugland, Modeling and Control of fertilizer granulation process

Explore the controllability of a granulation process in fertilizer production. Develop a model, fit it with plant data, and analyze system behavior. Investigate limit cycles, controller tuning, and stable particle balance. Further work includes controllability analysis and refining the control structure for enhanced efficiency.

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Christer Haugland, Modeling and Control of fertilizer granulation process

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  1. Controllability of a Granulation Process Christer Haugland Supervisors: Sigurd Skogestad Vidar Alstad (YaraTechnology Center) Christer Haugland, Modeling and Control of fertilizer granulation process

  2. Outline • Summaryprocessdescription • Obtaining limit cyclebehaviour as seen at theYara plant • Fitting model to plant data • Simulinkmodel • Furtherwork

  3. Process description • Feed: • Slurry melt • Spherodizer: • Drying • Granulation • Screens • Separation • basedonsize • Crusher • Crushoversize • particles

  4. Recycle mass flow controller • Split range controller

  5. Model • Modeldeveloped in MATLAB • First looked at discretizations in particle sizes • Increased particle classes (no. of discretizations) until the effect on the model was no longer seen. • Limit cycles occurred!

  6. Stable system. Crushed particle sizes = 2.55 mm

  7. Unstable system. Crushedparticlesizes = 1.55 mm

  8. Bifurcation plots d50_mill = 1.95 mm

  9. Plant data compared to model • Too large particle sizes in the system! • Only closed loop data available • Recycle mass flow controller output should also be in the same range as plant data. • Unknown controller tunings. Many unknown parameters

  10. Model fitted to plant data • Trial and error approach • Based on average values of plant data d50 and controller output values • Not able to get the same amplitude in d50 oscillations • Controller output and d50 in the same region as plant data.

  11. Model fitted to plant data Screen 2 Screen 1 New parameters Old parameters

  12. Simulink Model • Particle balance. Recycle controller off. • Particles inn-> Crusher , Particles out -> Product

  13. Simulink Model • Particle balance. Recycle controller on. • Keeping recycled particles constant -> Stable particle balance

  14. Further work • Bifurcation plots with the new model fitted to plant data • Controllability analysis • Look at control structure

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