DFSLIF: dynamical fuzzy system with linguistic information feedback

We propose a new dynamical fuzzy system with linguistic information feedback (DFSLIF). Instead of crisp system output, the delayed conclusion fuzzy membership function in the consequence part is fed back locally with adjustable scaling and shifting in order to overcome the static mapping drawback of conventional fuzzy systems. We give a detailed description of the corresponding structure and algorithm. Our novel scheme has the advantage of inherent dynamics, and is therefore well suited for handling temporal problems like dynamical system identification, control, and filtering. Simulation experiments have been carried out to demonstrate its effectiveness.

[1]  George C. Mouzouris,et al.  Dynamic non-Singleton fuzzy logic systems for nonlinear modeling , 1997, IEEE Trans. Fuzzy Syst..

[2]  Jie Zhang,et al.  Recurrent neuro-fuzzy networks for nonlinear process modeling , 1999, IEEE Trans. Neural Networks.

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

[4]  Chuen-Chien Lee FUZZY LOGIC CONTROL SYSTEMS: FUZZY LOGIC CONTROLLER - PART I , 1990 .

[5]  M. Sugeno,et al.  Structure identification of fuzzy model , 1988 .

[6]  Witold Pedrycz,et al.  Fuzzy sets in pattern recognition: Methodology and methods , 1990, Pattern Recognit..

[7]  P. S. Sastry,et al.  Memory neuron networks for identification and control of dynamical systems , 1994, IEEE Trans. Neural Networks.

[8]  Fei-Yue Wang,et al.  Linguistic dynamic systems and computing with words for complex systems , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[9]  Kevin M. Passino,et al.  Expert supervision of fuzzy learning systems for fault tolerant aircraft control , 1995 .

[10]  E. H. Mamdani,et al.  Application of Fuzzy Logic to Approximate Reasoning Using Linguistic Synthesis , 1976, IEEE Transactions on Computers.

[11]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[12]  J. Mendel Fuzzy logic systems for engineering: a tutorial , 1995, Proc. IEEE.

[13]  Ching-Hung Lee,et al.  Identification and control of dynamic systems using recurrent fuzzy neural networks , 2000, IEEE Trans. Fuzzy Syst..