Fuzzy Model Identification of a Biological Process Based on Input-Output Data Clustering

This paper deals with the application of fuzzy clustering techniques for the model identification of an enhanced FAMIMO biological wastewater treatment process from input-output data. This MIMO system is represented as a set of coupled MISO models of the Takagi-Sugeno type. A comparative study with two clustering algorithms for the construction of the fuzzy model is carried out. The Gustafson-Kessel (GK) algorithm and the so-called robust parallel competitive agglomerative (RPCA) algorithm are considered. From a biotechnological point of view, different simulation experiences were conducted integrating both continuous and batch modes in order to validate the obtained models. Results are reported and discussed

[1]  Robert Babuska.  Constructing Fuzzy Models from Partitions , 1998 .

[2]  Jun-Ichi Horiuchi,et al.  Fuzzy modeling and control of biological processes. , 2002, Journal of bioscience and bioengineering.

[3]  Michael Wagenknecht,et al.  Takagi-Sugeno fuzzy model development of batch biotechnological processes , 2001, Int. J. Approx. Reason..

[4]  Hichem Frigui,et al.  A Robust Competitive Clustering Algorithm With Applications in Computer Vision , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  J.J. Soriano,et al.  Robust agglomerative clustering algorithm for fuzzy modeling purposes , 2004, Proceedings of the 2004 American Control Conference.

[6]  Song-Shyong Chen,et al.  Robust TSK fuzzy modeling for function approximation with outliers , 2001, IEEE Trans. Fuzzy Syst..

[7]  J. A. Roubos,et al.  Identification of MIMO systems by input-output TS fuzzy models , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[8]  Donald Gustafson,et al.  Fuzzy clustering with a fuzzy covariance matrix , 1978, 1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes.

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

[10]  S Shioya,et al.  Knowledge-based design and operation of bioprocess systems. , 1999, Journal of bioscience and bioengineering.

[11]  T Yoshida,et al.  Knowledge-based control of fermentation processes. , 1992, Biotechnology and bioengineering.