An Integrated Identification and Control Design Methodology for Multivariable Process System Applications

IEEE Control Systems

Volumn 20, Issue 3, 2000, Pages 25-37

  Rivera, Daniel E ^a   Jun, Kyoung S ^b  

^a Arizona State University   (United States)

^b SAMSUNG Electronics   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

CONTROL SYSTEM ANALYSIS; CONTROL SYSTEM SYNTHESIS; INTEGRATED CONTROL; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; MULTIVARIABLE CONTROL SYSTEMS; PARAMETER ESTIMATION; PREDICTIVE CONTROL SYSTEMS; REGRESSION ANALYSIS; THREE TERM CONTROL SYSTEMS;

AUTOREGRESSIVE WITH EXTERNAL INPUT (ARX) ESTIMATION; MODEL PREDICTIVE CONTROL (MPC); MULTI-INPUT MULTI-OUTPUT (MIMO) SYSTEMS; PSEUDORANDOM BINARY SEQUENCE (PRBS);

PROCESS CONTROL;

EID: 0033738163     PISSN: 1066033X     EISSN: None     Source Type: Journal    
DOI: 10.1109/37.845036     Document Type: Article

References (14)

1. L. Ljung, System Identification Theory for the User, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall, 1999.
2. Y.C. Zhu, A.C.P.M. Backx, and P. Eykhoff, “Multivariable process identification based on frequency domain measures,” in Proc. 30th Conf. Decision and Control, Brighton, 1991, pp. 303-308.
3. D.M. Preit and C. E. Garcia, The Second Shell Process Control Workshop. London: Butterworths, 1990.
4. K. Weisehedel and T.J. McAvoy, “Feasability of decoupling in conventionally controlled distillation columns,” Ind. Eng. Chem. Fund., vol. 19, pp. 379, 1980.
5. H. Chien and B.A. Ogunnaike, “Modeling and control of a temperature-based high-purity distillation column,” Chem. Eng. Comm., vol. 158, pp. 71-195, 1997.
6. I. Ljung, System Identification Toolbox User's Guide. Natick, MA: MathWorks, 1995.
7. D.F. Rivera and S.V. Galkwad, “Systematic techniques for determining modelling requirements for SISO and MIMO feedback control,” J. Proc. Cont., vol. 5, pp. 213-224, 1995.
8. S.V. Gaikwad and D.F. Rivera, “Control-relevant input signal design for multivariable system identification: Application to high-purity distillation,” in Proc. IFAC World Congr., vol. M, San Francisco, CA, 1996, pp. 349-354.
9. M. Morari and E. Zafiriou, Robust Process Control, Englewood Cliffs, NJ, Prentice-Hall, 1989.
10. D.E. Rivera, M. Morari, and S. Skogestad, “Internal model control, 4. PID controller design,” Ind. Eng. Chem. Process Des. Dev., vol. 25, pp. 252-265, 1986.
11. 1 and μ-controller synthesis,” Int. J. Contr., vol. 46, pp. 505-527, 1987.
12. W.H. Ray, Advanced Process Control. New York: McGraw-Hill, 1981.
13. S. Adusumilli, D.E. Rivera, S. Dash, and K. Tsakalis, “Integrated MIMO identification and robust PID controller design using loop shaping,” in Proc. 1998 American Control Conf., Philadelphia, PA, 1998, pp. 1230-1234.
14. J.H. Lee, M. Morari, and C.F. Garcia, “State-space interpretation of model predictive control,” Automatica, vol. 30, pp. 707-714, 1994.