Process control using a CFCM-based on-line adaptive neuro-fuzzy systems

A conditional fuzzy c-means (CFCM)-based fuzzy adaptive neuro-fuzzy system (ANFS) by on-line learning is proposed in this paper. In the structure identification, the optimal or near optimal number of fuzzy rules is determined by a CFCM clustering with TSK-type fuzzy rules based on the criterion. In the parameter identification. The consequent parameters are tuned by least squares estimator (LSE) and the premise parameters are tuned by back-propagation algorithm in off-line learning. Then on-line learning by recursive least squares estimator (RLSE) and back-propagation algorithm is used to cope with time varying plant dynamics. Finally, we show its capability for a CFCM-based on-line ANFS to control the temperature of a water path.

[1]  Chuen-Tsai Sun,et al.  Rule-base structure identification in an adaptive-network-based fuzzy inference system , 1994, IEEE Trans. Fuzzy Syst..

[2]  Ebrahim H. Mamdani,et al.  An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller , 1999, Int. J. Hum. Comput. Stud..

[3]  Michio Sugeno,et al.  A fuzzy-logic-based approach to qualitative modeling , 1993, IEEE Trans. Fuzzy Syst..

[4]  Sigeru Omatu,et al.  Process control by on-line trained neural controllers , 1992, IEEE Trans. Ind. Electron..

[5]  野崎 賢,et al.  Generating Fuzzy Rules from Numerical Data , 1995 .

[6]  Chin-Teng Lin,et al.  A neural fuzzy control system with structure and parameter learning , 1995 .

[7]  Chin-Teng Lin,et al.  Neural fuzzy systems , 1994 .

[8]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[9]  Jerry M. Mendel,et al.  Generating fuzzy rules by learning from examples , 1992, IEEE Trans. Syst. Man Cybern..

[10]  Chin-Teng Lin,et al.  An online self-constructing neural fuzzy inference network and its applications , 1998, IEEE Trans. Fuzzy Syst..

[11]  Witold Pedrycz,et al.  Conditional fuzzy clustering in the design of radial basis function neural networks , 1998, IEEE Trans. Neural Networks.

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

[13]  Euntai Kim,et al.  A new approach to fuzzy modeling , 1997, IEEE Trans. Fuzzy Syst..