Temperature control of industrial gas phase propylene polymerization in fluidized bed reactors using model predictive control
Two-phase dynamic model describing gas phase propylene polymerization in a fluidized bed reactor was used to explore the dynamic behavior and process control of the reactor temperature by manipulating the catalyst feed rate and reactor cooling water flow. The analysis was performed using a two phase...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/12882/1/543.pdf http://eprints.um.edu.my/12882/ |
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| Institution: | Universiti Malaya |
| Language: | English |
| Summary: | Two-phase dynamic model describing gas phase propylene polymerization in a fluidized bed reactor was used to explore the dynamic behavior and process control of the reactor temperature by manipulating the catalyst feed rate and reactor cooling water flow. The analysis was performed using a two phase model, the presence of particles in the
bubbles and the excess gas in the emulsion phase and consequently polymerization reaction in both phases were considered. A model predictive control (MPC) technique is implemented to control of the nonlinear process and compared its performance with conventional PI controllers tuned using the Internal Model Control (IMC) method as well as the standard Ziegler-Nichols (Z-N) method. The closed-loop simulations revealed that the Z-N PI controller produced oscillatory responses and the MPC and the IMC-Based PI controllers were able to track the changes in the set point. However the quality of the MPC set point tracking was superior to that of the IMC-Based PI controller. |
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