Dynamic Modeling and Model Predictive Control for Packed Reactive Distillation Processes

1. Dynamic Modeling and Model Predictive Control for Packed Reactive Distillation Processes Presented by: Sebastien Lextrait Advisor: Dr. Thomas F. Edgar

2. Control Issues • Difficulties with traditional controllers • Purity and reactant conversion • Multiple steady states • Limitations of traditional feedback controllers • Advanced control schemes • Dynamic matrix control method • Output feedback control scheme for some high index DAEs • Nonlinear model predictive control strategy

3. Control Issues • Investigation of MPC control strategy • Performance dependence on model complexity • Problem formulation • On-line implementation not addressed • Computational time • Experimental validation of proposed control schemes

4. Models of Different Complexity • Equilibrium versus rate-based dynamic models • Physical properties • Hydraulic models • Liquid holdup • Vapor holdup • Vapor pressure drop • Catalyst description • Diffusion limitations

5. Validation and Behavior Analysis • Experimental data • Steady-state • Dynamic • Study the effect of modeling assumptions on the overall model behavior • Computational time • Response accuracy

6. Investigation of MPC strategy • Nonlinear programming problem • Investigate state estimation and observer issues for this process • NMPC versus PID and linear MPC • Commercial Software Packages • Aspen Technology • Dot Products

7. Controller Implementation and Experimental Validation • Numerical simulations • Real-time optimization issues • Pilot Plant Testing • Interface NOVA to Fisher Rosemount DeltaV distributed control system

8. Pilot scale TAME reactive distillation column

9. Conclusions • Dynamic modeling of packed reactive distillation required • Investigation of MPC strategy for this non-traditional chemical process • Adapt control scheme for on-line use • Validation with experimental data