Sensitivity-based solution updates in closed-loop dynamic optimization

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 37, Issue 9, 2004, Pages 947-952

  Kadam, Jitendra V ^a   Marquardt, Wolfgang ^a  

^a RWTH AACHEN UNIVERSITY   (Germany)

Author keywords

Dynamic real time optimization; Input adaptation; Parametric sensitivity analysis; Uncertainty; Unknown active set

Indexed keywords

BATCH REACTORS; UNCERTAINTY ANALYSIS;

ACTIVE CONSTRAINTS; CLOSED LOOP DYNAMIC; CLOSED LOOP OPTIMIZATION; COMPUTATIONAL EXPENSE; PARAMETRIC SENSITIVITY; PARAMETRIC UNCERTAINTIES; REAL-TIME OPTIMIZATION; UNCERTAIN PARAMETERS;

REAL TIME SYSTEMS;

EID: 85056885654     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. Backx, T., O. Bosgra and W. Marquardt (1998). Towards intentional dynamics in supply chain conscious process operation. In: FO-CAPO 98, Snowbird, Utah, www.lpt.rwthaachen.de/Publication/Techreport/l998/LPT-1998-25.html.
2. Binder, T., L. Blank, W. Dahmen and W. Marquardt (2002). Online Optimization of Large Scale Systems. Chap. Multiscale concepts for moving horizon optimization, pp. 341-361. Springer.
3. Büskens, C. and H. Maurer (2002), Online Optimization of Large Scale Systems, Chap. Sensitivity analysis and real-time optimization of parametric nonlinear-programming problems, pp. 3-16. Springer.
4. Diehl, M., H.G. Bock, J.P. Schbder, R. Findeisen, Z. Nagy and F. Allgower (2002). Real-time optimization and nonlinear model predictive control of processes governed by differential-algebraic equations. Journal of Process Control 12(4), 577-585.
5. DyOS (2002). DyOS User Manual, Release 2.1. Lehrstuhl für Prozesstechnik, RWTH Aachen University. Aachen, Germany.
6. Fiacco, A. V. (1983). Introduction to Sensitivity and Stability Analysis in Nonlinear Programming. Academic Press, New York.
7. Forbes, J. Fraser (1994). Model structure and adjustable parameter selection for operations optimizations. PhD thesis. McMaster University.
8. Ganesh, N. and L. T. Biegler (1987). A reduced Hessian strategy for sensitivity analysis of optimal flowsheets. AICHE J. 33(2), 282-296.
9. Kadam, J. V, and W. Marquardt (2003). A strategy for update of dynamic optimization solution in the presence of uncertainty. Technical report. Lehrstuhl für Prozesstechnik, RWTH Aachen University.
10. Kadam, J. V., W. Marquardt, M. Schlegel, R.L. Tousain, D.H. van Hessem, J. van den Berg and O. H. Bosgra (2002). A two-level strategy of integrated optimization and control of industrial processes: a case study. In: European Symposium on Computer Aided Process Engineering - 12 (J. Grievink and J. V. Schijndel, Eds.). Elsevier, pp. 511 516.
11. Kraft, D. (1985). On converting optimal control problems into nonlinear programming problems. Comput. Math. Prog. 15, 261-280.
12. Nocedal, J. and S.J. Wright (1999). Numerical Optimization. Springer-Verlag.