New Concepts for the Estimation of Takagi-Sugeno Model Based on Extended Kalman Filter - Fuzzy Modeling and Control: Theory and Applications - page 22

References
Al-Hadithi, B. M., Jiménez, A., & Matía, F. (2011). New methods for the estimation of T-S model
based extended Kalman filter and its applications to optimal control for nonlinear systems. Opti-
mal Control, Applications and Methods , 33 , 552-575 (Published online in Wiley InterScience)
Al-Hadithi, B. M., Jiménez, A., &Matía, F. (2012). A new approach to fuzzy estimation of Takagi-
Sugeno model and its applications to optimal control for nonlinear systems. Applied Soft Com-
puting , 12 , 280-290.
Cao, S. G., Rees, N. W., & Feng, G. (1997). Analysis and design for a class of complex control
systems- part i: Fuzzy modeling and identification. Automatica , 33 , 1017-1028.
Chen, B., Xiaoping, L., & Shaocheng, T. (2007). Adaptive fuzzy output tracking control of MIMO
nonlinear uncertain systems. IEEE Transactions on Fuzzy Systems , 15 (2), 287-300.
Chen, W., & Saif, M. (2005). A novel fuzzy system with dynamic rule base. IEEE Transactions on
Fuzzy Systems , 13 (5), 569-582.
Cordon, O., Herrera, F., Magdalena, L., & Villar, P. (2001). A genetic learning process for the
scaling factors, granularity and contexts of the fuzzy rule-based system data base. Information
Sciences , 136 , 85-107.
Gang, F. (2006). A survey on analysis and design of model-based fuzzy control systems. IEEE
Transactions on Fuzzy Systems , 14 (5), 676-697.
Gillespie, T. D. (1992). Fundamentals of vehicle dynamics . Warrendale: Society of Automotive
Engineers Inc.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization & machine learning . Cambridge:
Addison-Wesley.
Guerra, T. M., & Vermeiren, L. (2004). Lmi-based relaxed nonquadratic stabilization conditions
for nonlinear systems in the Takagi-Sugeno's form. Automatica , 40 , 823-829.
Herrera, F., Lozano, M., & Verdegay, J. L. (1995). Tuning fuzzy logic controllers by genetic algo-
rithms. International Journal of Approximate Reasoning , 12 (3-4), 299-315.
Holland, J. H. (1992). Adaptation in natural and artificial systems . MIT Press. ISBN0-262-58111-6.
Hong, T. P., & Lee, C. Y. (1996). Induction of fuzzy rules and membership functions from training
examples. Fuzzy Sets System , 84 (1), 33-47.
Hou, Y., Jacek,M., Zurada,W., Karwowski,W. S., &Davis, K. (2007). Identification of key variables
using fuzzy average with fuzzy cluster distribution. IEEE Transactions on Fuzzy Systems , 15 (4),
673-685.
Hseng, T., Li, S., & Tsai, S.-H. (2007). Fuzzy bilinear model and fuzzy controller design for a class
of nonlinear systems. IEEE Transactions on Fuzzy Systems , 15 (3), 494-506.
Jae-Hun, K., Hyun, C.-H., Kim, E., & Park, M. (2007). New adaptive synchronization of uncertain
chaotic systems based on T-S fuzzy model. IEEE Transactions on Fuzzy Systems , 15 (3), 359-369.
Jiang, X., & Han, Q.-L. (2007). Robust H ∞ control for uncertain Takagi-Sugeno fuzzy systems
with interval time-varying delay. IEEE Transactions on Fuzzy Systems , 15 (2), 321-331.
Jiménez, A., Al-Hadithi, B. M., & Matía, F. (2012). Improvement of Takagi-Sugeno fuzzy model
for the estimation of nonlinear functions. Asian Journal of Control , 14 (6), 1-15.
Johansen, T. A., Shorten, R., & Murray-Smith, R. (2000). On the interpretation and identification
of dynamic Takagi-Sugeno models. IEEE Transactions on Fuzzy Systems , 8 (3), 297-313.
Kalman, R. E. (1960). A new approach to linear filtering and prediction problems. Transactions on
ASME-Journal of Basic Engineering , 82 (series D), 35-45.
Kotwicki, A. J. (1982). Dynamic models for torque converter equipped vehicles , Technical report.
Warrendale: Society of Automotive Engineers Inc.
Kumar, M., Stoll, R., & Stoll, N. (2006). A min-max approach to fuzzy clustering, estimation, and
identification. IEEE Transactions on Fuzzy Systems , 14 (2), 248-262.
Lee, T. C., Yang, D. R., Lee, K. S., & Yoon, T. W. (2001). Indirect adaptive backstepping control
of a pH neutralization process based on recursive prediction error method for combined state and
parameter estimation. Industrial and Engineering Chemistry Research , 40 , 4889-4901.