Pattern-based fuzzy predictive control for a chemical process with dead time

Engineering Applications of Artificial Intelligence

Volumn 13, Issue 1, 2000, Pages 37-45

  Zhao, Futao ^a   Ou, Jing ^b   Du, Wei ^a  

^a ZHEJIANG UNIVERSITY   (China)

^b Oklahoma State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; CONTROL SYSTEM ANALYSIS; FUZZY CONTROL; FUZZY SETS; MATHEMATICAL MODELS; PROCESS CONTROL;

PATTERN-BASED FUZZY PREDICTIVE CONTROL;

PREDICTIVE CONTROL SYSTEMS;

EID: 0033906313     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0952-1976(99)00035-4     Document Type: Article

References (22)

1. Al-Sunni F., Al-Nemer T. A Smith Predictor FL-based controller for process with long dead time. Int. J. Systems Science. 28:(12):1997;1251-1258.
2. Aoki S., Kawachi S., Sugeno M. Application of fuzzy control logic for dead time processes in a glass melting furnace. Fuzzy Sets and Systems. 38:(3):1990;251-265.
3. Astrom K.J., Wittenmark B. Adaptive Control. 1989;Addison-Wesley, MA.
4. Bristol E.H. Pattern recognition: an alternative to parameter identification in adaptive control. Automatica. 13:(2):1977;197-202.
5. Cooper D.J., Hind R.F. Jr., Megan L. Pattern-based adaptive process control. Computers Chem. Engng. 14:(12):1990;1339-1350.
6. Giles R.F., Bartley T.M. Gain-adaptive deadtime compensation, ISA Transactions. 16:(1):1977;59-64.
7. Horn I.G. Improved filter design in internal model control. Ind. Eng. Chem. Res. 35:(10):1996;3437-3441.
8. Jang M.J., Chen C.L. Fuzzy successive modelling and control for time-delay system. Int. J. Systems Science. 27:(12):1996;1483-1490.
9. Kraus T.W., Myron T.J. Self-tuning PID controller use pattern recognition approach. Control Engineering. 31:(6):1984;106-111.
10. Lee C.C. Fuzzy logic controller-parts I and II. IEEE Trans. Systems, Man and Cybernetics. 20:(2):1990;404-435.
11. Meyer C., Seborg D.E., Wood R.K. A comparison of the Smith Predictor and conventional feedback control. Chemical Engineering Science. 31:(9):1976;775-778.
12. Morari M., Zafiriou E. Robust Process Control. 1989;Prentice-Hall, Englewood Cliffs, NJ.
13. Rengaswamy R., Venkatasubramanian V. A syntactic pattern-recognition approach for process monitoring and fault diagnosis. Engng. Applic. Artif. Intell. 8:(1):1995;35-51.
14. Seborg D.E., Edgar T.F., Mellichamp D.A. Process Dynamics and Control. 1989;Wiley, NY.
15. Seem J.E. A new pattern recognition adaptive controller with application to HVAC systems. Automatica. 34:(8):1998;969-982.
16. Shen G.C., Lee W.K. A predictive approach for adaptive inferential control. Computers Chem. Engng. 13:(6):1989;687-701.
17. Shinskey F.G. Process Control System. 3rd ed :1988;McGraw-Hill, NY.
18. Smith O.J. Closer control of loops with dead time. Chem. Eng. Process. 53:(5):1957;217-219.
19. Takagi T., Sugeno M. Fuzzy identification of systems and its applications to modeling and control. IEEE Trans. Systems, Man, Cybernetics. 15:(1):1985;116-132.
20. Vandeursen J.E., Peperstraete J.A. Model-based and PID controllers for disturbance rejection in processes with time delay: a comparison. ISA Transactions. 35:(2):1996;225-236.
21. Wellons M.C., Edgar T.F. The generalized analytical predictor. Ind. Eng. Chem. Res. 26:(8):1987;1523-1536.
22. Zhao F., Du W., Yu G. An improvement of generalized analytical predictor for chemical process control. Journal of Process Control. 9:(2):1999;185-191.