Internal model control design for transition control

The problem of controlling processes with a wide range of operating conditions is addressed. The process dynamics is represented by the weighted-sum of the linear model by using model validity functions. By treating the validity functions as uncertainties in the system, an internal model control (IMC) design strategy is developed for a particular class of nonlinear systems. Robust stability analysis under mixed time-varying and time-invariant uncertainties is presented. Simulation results confirm that the proposed IMC design method is indeed superior to its conventional counterpart.

[1]  T. Johansen,et al.  Constructing NARMAX models using ARMAX models , 1993 .

[2]  Gang Feng,et al.  An approach to H∞ control of a class of nonlinear systems , 1996, Autom..

[3]  Evanghelos Zafiriou,et al.  Robust process control , 1987 .

[4]  K. Poolla,et al.  Robust performance against time-varying structured perturbations , 1995, IEEE Trans. Autom. Control..

[5]  S. S. Rappaport,et al.  Multiple call hand-off problem with queued hand-offs and mixed platform types , 1995 .

[6]  Andrew Packard,et al.  The complex structured singular value , 1993, Autom..

[7]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[8]  J. A. Romagnoli,et al.  A nonlinear control design approach based on multi-linear models , 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).

[9]  J. Shamma.  Robust stability with time-varying structured uncertainty , 1994, IEEE Trans. Autom. Control..

[10]  Y. Arkun,et al.  Estimation of nonlinear systems using linear multiple models , 1997 .

[11]  Tor Arne Johansen,et al.  Operating regime based process modeling and identification , 1997 .

[12]  Fernando Paganini,et al.  Robust stability under mixed time-varying, time-invariant and parametric uncertainty , 1996, Autom..

[13]  Dale E. Seborg,et al.  Application of a general multi-model approach for identification of highly nonlinear processes-a case study , 1993 .

[14]  M. A. Henson,et al.  An internal model control strategy for nonlinear systems , 1991 .