Assessment and Future Directions of Nonlinear Model Predictive ...

482 A. Küpper and S. Engellτ [min]Q De[ml/min]Q Re[ml/min]Q Ra[ml/min]Pur Ex[%]Prod. [−]15105manipulated variable00 50 100 150 200 250 3001510500 50 100 150 200 250 30010500 50 100 150 200 250 30010500 50 100 150 200 250 30010.500 50 100 150 200 250 30010095constraintconstraint requirement900 50 100 150 200 250 300Period NumberFig. 4. Simulation of the predictive controller; manipulated variables and constraintsprocess converges to a stationary operating point. The optimizer converges tothe optimum within one sampling time, and hence, can be applied in real-time.5 ConclusionAn online model-based optimization and parameter estimation scheme for theHashimoto Simulated Moving Bed process has been presented. The approachhas the advantage that the process is automatically operated at its economicoptimum while the purity and productivity requirements and plant limitationsare fulfilled. In future research, the application to a pilot-plant is planned.AcknowledgementWe would like to thank Larry Biegler for a fruitful discussion about how to avoidzero gradient information for a SQP solver. This investigation was supported bythe Deutsche Forschungsgemeinschaft (DFG) under grant DFG En 152/34. Thissupport is gratefully acknowledged.References[1] Hashimoto, K., Adachi, S., Noujima, H. and Ueda, Y., “A New Process CombiningAdsorption and Enzyme Reaction for Producing Higher-Fructose Syrup”,Biotechnology and Bioengineering, Vol. 25, pp. 2371-2393, (1983).