[Angelov, P. P. and Filev, D. P. (2004). An approach to online identification of Takagi-Sugeno fuzzy models, IEEE Transactions on System, Man and Cybernetics—Part B: Cybernetics 34(1): 484-498.10.1109/TSMCB.2003.817053]Search in Google Scholar
[Bezdek, J. (1974). Comparing different approaches to model error modeling in robust identification, Journal of Cybernetics 3(3): 58-71.]Search in Google Scholar
[Chen, F. and Khalil, H. (1995). Adaptive control of a class of nonlinear discrete-time systems using neural networks, IEEE Transactions on Automatic Control 40(5): 791-801.10.1109/9.384214]Search in Google Scholar
[Chien, C.-J., C.-T. H. and Yao, C.-Y. (2004). Fuzzy system-based adaptive iterative learning control for nonlinear plants with initial state errors, IEEE Transactions on Fuzzy Systems 12(5): 724-732.10.1109/TFUZZ.2004.834806]Search in Google Scholar
[Chiu, S. L. (1994). Fuzzy model identification based on cluster estimation, International Journal of Fuzzy Systems 2: 267-278.10.3233/IFS-1994-2306]Search in Google Scholar
[Gao, Y. and Er, M. J. (2003). Online adaptive fuzzy neural identification and control of a class of MIMO nonlinear systems, IEEE Transactions on Fuzzy Systems 11(4): 462-477.10.1109/TFUZZ.2003.814833]Search in Google Scholar
[Gustafson, D. E. and Kessel, W. C. (1979). Global random optimization by simultaneous perturbation stochastic approximation, Proceedings of the IEEE Control Decision Conference, San Diego, CA, USA, pp. 761-766.]Search in Google Scholar
[Hao, Y. (1998). General SISO Takagi-Sugeno fuzzy system with linear rule consequent are universal approximators, IEEE Transactions on Fuzzy Systems 6(4): 582-587.10.1109/91.728456]Search in Google Scholar
[Hao, Y., Y. D.-S. L. and Shao, S. (1999). Comparison of necessary conditions for typical Takagi-Sugeno and Mamdani fuzzy systems as universal approximators, IEEE Transactions on System, Man and Cybernetics—Part B: Cybernetics 29(5): 508-514.10.1109/3468.784177]Search in Google Scholar
[Ogata, K. (1995). Discrete-time Control System, 2nd Ed., Prentice-Hall, Upper Saddle River, NJ.]Search in Google Scholar
[Park, C.-W. and Cho, Y.-W. (2004). T-S model based indirect adaptive fuzzy control using online parameter estimation, IEEE Transactions on System, Man and Cybernetics—Part B: Cybernetics 34(6): 2293-2302.10.1109/TSMCB.2004.83507915619930]Search in Google Scholar
[Phan, P. A. and Gale, T. J. (2008). Direct adaptive fuzzy control with a self-structuring algorithm, Fuzzy Sets and Systems 159(8): 871-899.10.1016/j.fss.2007.09.012]Search in Google Scholar
[Qi, R. and Brdys, M. A. (2008). Stable indirect adaptive control based on discrete-time T-S fuzzy model, Fuzzy Sets and Systems 159(8): 900-925.10.1016/j.fss.2007.08.009]Search in Google Scholar
[Wang, L. (1994). Adaptive Fuzzy System and Control: Design and Stability Analysis, Prentice-Hall, Englewood Cliffs, NJ.]Search in Google Scholar