Abstract
Robust operation of complex nonlinear and time varying processes create several challenges for the multivariable control system design engineer. Optimal controller designs are typically model based and a design that delivered excellent performance under nominal conditions may produce poor results for nonlinear systems when operating conditions are varied. Changes in operating conditions may occur through a setpoint change or nonstation-ary disturbance. Setpoint changes to produce different grades of products and nonstationary disturbances such as variations in input properties are common in many process industries. When such changes occur, the control system may have poor performance since the original process representation can become inaccurate. In addition, any sensor or actuator faults can degrade multivariable control system performance.
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References
T.L. Trankle and J. D. Pehoushek, ”ACOLADES: A control law designing expert system,” in Proc. IEEE 3rd Symp. on Computer Aided Control System Design, pp. 150–157, 1986.
R.E. Smith and W.H. Ray, ”An expert system for automated computer-aided control system design,” 1990 AIChE Annual MeetingChicago, IL, Paper No. 312Q, November 1990.
G.K.H. Pang and A.G.J. MacFarlane, An Expert Systems Approach to omputer-Aided Design of Multivariable Systems, Heidelberg, Germany: Springer-Verlag, 1987.
K. J. Åström, J. J. Anton, and K. E. Arzen, ”Expert Control,” Automatical,, Vol. 22, pp. 277–286, 1986.
K.E. Arzen, ”An architecture for expert system based feedback control,” Automatica, Vol. 25, pp. 813–827, 1989.
R.L. Moore, L.B. Hawkinson, M. Lewin, A.G. Hoffman, B.L. Matthews and M.H. David, ”Expert systems methodology for real-time process control,” in Prepr. 1987 IFAC 10th World Congress, Munich, Germany, vol. 6, pp. 274–281, 1987.
M. R. Basila, A. Çmar, and G. Stefanek ”MOBECS: model-object based expert control system,” Comput. chem,. Engng, Vol. 14, pp. 551-560, 1990.
D.C. Youla, H. A. Jabr, and J. J. Bongiorno, ”Modern Wiener-Hopf design of optimal controllers, part II: The multivariable case. IEEE Trans. Autom. Control,, Vol. AC-26, pp. 319–338, 1976.
G. Zames, “Feedback and optimal sensitivity: Model reference transformations, multiplicative seminorms, and approximate inverses,” IEEE Trans. Autom. Control, Vol. AC-26, pp. 301–320, 1981.
J. Doyle and G. Stein, ”Multivariable feedback design: Concepts for a classical/modern synthesis. IEEE Trans. Autom,. Control,, Vol. AC-26, pp. 4–16, 1981.
J. M. Maciejowski, Multivariable Feedback Design. New York, New York: Addison-Wesley Publishing Company, 1989.
B.A. Francis, A Course In H∞ Control Theory. Heidelberg, Germany: Springer-Verlag, 1987.
R.A. Adomaitis, and A. Çmar, ”The bifurcation behavior of an autothermal packed bed tubular reactor. Chem. Engng. Sci., Vol. 43, pp. 887–898, 1988.
B. W. Bequette, ”Nonlinear control of chemical processes: a review,” Ind. Eng. Chem. Res., Vol. 30, pp. 1391–1413, 1991.
S. J. Kendra, M. R. Basila, and A. Çinar, ”Intelligent process control with supervisory knowledge-based systems,” IEEE Control Systems Vol. 14, pp. 37–47, 1994.
S. J. Kendra and A. Çinar, submitted to J. Process Control, 1996.
Neuron Data, Inc. Nexpert Object — Fundamentals, Palo Alto, CA, 1987.
R.W. Chylla, Design and control of tubular autothermal reactors. Ph.D. Thesis, Illinois Institute of Technology, 1987.
B.C. Moore, ”Principal component analysis in linear systems: Controllability, observability, and model reduction,” IEEE Trans. Autom. Control, Vol. AC-26, pp. 17–32, 1981.
K. Glover, ”All optimal Hankel-norm approximations Of linear multivariable systems and their L∞-error bounds,” Int. J. Control, Vol. 39, pp. 1115–1193, 1984.
M.G. Safonov and R. Y. Chiang, ”Model reduction for robust control: A Schur relative error method,” In Proc. Amer. Control Conf., Atlanta, GA, pp. 1685–1690, 1987.
S.J. Kendra, Robust Multivariable Controller Design In Intelligent Control By Knowledge Based Systems. Ph.D. Thesis, Illinois Institute of Technology, 1992.
X. Wu and A. Çinar, ”Integrated nonlinear model identification and outlier detection in time series,” 1993 AIChE Annual Meeting, St. Louis, MO, Paper No. 145e, November 1993.
Gensym Corporation, G2 Reference Manual, Cambridge, MA, 1989.
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Kendra, S.J., Basila, M.R., Çinar, A. (1997). Intelligent Process Control with Supervisory Knowledge-Based Systems. In: Tzafestas, S.G. (eds) Methods and Applications of Intelligent Control. Microprocessor-Based and Intelligent Systems Engineering, vol 16. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-5498-7_5
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DOI: https://doi.org/10.1007/978-94-011-5498-7_5
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