Dantzig-Wolfe decomposition and plant-wide MPC coordination

Computers and Chemical Engineering

Volumn 32, Issue 7, 2008, Pages 1507-1522

  Cheng, Ruoyu ^a   Fraser Forbes, J ^a   Yip, W San ^b  

^a UNIVERSITY OF ALBERTA   (Canada)

^b SUNCOR ENERGY INC   (Canada)

Author keywords

Complexity analysis; Coordination; Dantzig Wolfe decomposition; Decentralized MPC

Indexed keywords

AUTONOMOUS AGENTS; COMPUTATION THEORY; COMPUTER ARCHITECTURE; IDENTIFICATION (CONTROL SYSTEMS);

COMPLEXITY ANALYSIS; DANTZIG-WOLFE DECOMPOSITION; DECENTRALIZED MPC;

MODEL PREDICTIVE CONTROL;

AUTONOMOUS AGENTS; COMPUTATION THEORY; COMPUTER ARCHITECTURE; IDENTIFICATION (CONTROL SYSTEMS); MODEL PREDICTIVE CONTROL;

EID: 43049099009     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compchemeng.2007.07.003     Document Type: Article

References (20)

1. Andrei N. On the complexity of MINOS package for linear programming. Studies in Informatics and Control 13 (2004) 35-46
2. Camponogara E., Jia D., Krogh B.H., and Talukdar S. Distributed model predictive control. IEEE Control Systems Magazine 0272-1708/02 (2002) 44-52
3. Cheng R., Forbes J.F., and Yip W.S. Dantzig-Wolfe decomposition and large-scale constrained MPC problems. Proceedings of the DYCOPS 7. Boston, USA (2004)
4. Cheng R., Forbes J.F., Yip W.S., and Cresta J.V. Plant-wide MPC: A cooperative decentralized approach. Proceedings of the 2005 IEEE-IAS APC. Vancouver, Canada (2005)
5. Chvatal V. Linear Programming (1983), W. H. Freeman and Company
6. Dantzig G.B., and Thapa M.N. Linear programming 2: Theory and extensions (2002), Springer Verlag
7. Dantzig G.B., and Wolfe P. Decomposition principle for linear programs. Operation Research 8 (1960) 101-111
8. Gilmore P.C., and Gomory R.E. A linear programming approach to the cutting stock problem. Operation Research 9 (1961) 849-859
9. Havlena V., and Lu J. A distributed automation framework for plant-wide control, optimization, scheduling and planning. Proceedings of the 16th IFAC world congress 2005. Prague, Czech (2005)
10. Herbst J.A., and Pate W.T. Overcoming the challenges of plantwide control. Emerging separation technologies for metals II. Hawaii, USA (1996) 3-13
11. Kadam J.V., Schlegel M., Marguardt W., Tousain R.L., Hesssem D.H.V., Berg J.V.D., and Bosgra O.H. A two-level strategy of integrated dynamic optimization and control of industrial processes - a case study. Proceedings of the European symposium on computer aided process engineering, 12 (2002), Elsevier 511-516
12. Kassmann D.E., Badgwell T.A., and Hawkins R.B. Robust steady-state target calculation for model predictive control. AIChE Journal 46 (2000) 1007-1024
13. Lasdon L.S. Optimization theory for large scale systems. 2nd ed. (2002), Dover Publications Inc
14. Lestage R., Pomerleau A., and Hodouin D. Constrained real-time optimization of a grinding circuit using steady-state linear programming supervisory control. Power Technology 124 (2002) 254-263
15. Lu J.Z. Challenging control problems and emerging technologies in enterprise optimisation. Control Engineering Practice 11 (2003) 847-858
16. Nash S.G., and Sofer A. Linear and nonlinear programming. 1st ed. (1996), McGraw-Hill
17. Qin S.J., and Badgwell T.A. A survey of industrial model predictive control technology. Control Engineering Practice 11 (2003) 733-764
18. Scheiber S. Decentralized control. Control Engineering (2004) 44-47
19. Venkat A.N., Rawlings J.B., and Wright S.J. Plant-wide optimal control with decentralized mpc. Proceedings of the DYCOPS 7. Boston, USA (2004)
20. Ying C., and Joseph B. Performance and stability analysis of LP-MPC and QP-MPC cascade control systems. AIChE Journal 45 (1999) 1521-1534