Fuzzy system identification and predictive control of load system in power plant

We use the T-S fuzzy model to express dynamic systems, and present an online identification algorithm for its parameters and structures. A multivariable fuzzy generalized predictive control approach is put forward based on the identified fuzzy model by means of Clark's principle of single-variable generalized predictive control, some of whose performances are analyzed in detail. A simulation study for the multivariable load control system of an electric generating unit shows that the approach is superior to a conventional load control system.

[1]  D. Siljak,et al.  On stability of interval matrices , 1994, IEEE Trans. Autom. Control..

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

[3]  Notes on multivariable fuzzy controller under Gödel's implication , 1997 .

[4]  David W. Clarke,et al.  Generalized predictive control - Part I. The basic algorithm , 1987, Autom..

[5]  J. T. Spooner,et al.  Direct adaptive fuzzy control for a class of discrete-time systems , 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).

[6]  R. Langari,et al.  A decomposition approach for fuzzy systems identification , 1995, Proceedings of 1995 34th IEEE Conference on Decision and Control.

[7]  Liao Xiao Xin,et al.  Stability of interval matrices , 1987 .