An efficient method to represent and process imprecise knowledge

We are primarily concerned with the problem of representing imprecise statements and knowledge as well as drawing conclusions based on this type of knowledge. Our particular interest is to establish an efficient method, capable to represent and apply (i.e. reason with) imprecise knowledge within real problems. In the present paper we first introduce an axiomatic framework and discuss it with illustrative examples. One suggestion for an application-oriented specialization is given by scalar fuzzy control (SFC), which is presented in the second part of this paper. After the introduction of the SFC theory, it is proofed that it is a member of the axiomatic framework. Its usage is finally illustrated by applying it to the well known inverted pendulum problem.

[1]  Hans-Jürgen Zimmermann,et al.  An application-oriented view of modeling uncertainty , 2000, Eur. J. Oper. Res..

[2]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[3]  George Boole,et al.  The mathematical analysis of logic , 1948 .

[4]  Stanley L. Hurst,et al.  Multiple-Valued Logic—its Status and its Future , 1984, IEEE Transactions on Computers.

[5]  E. Sha,et al.  Minimization of fuzzy systems based on fuzzy inference graphs , 1996, 1996 IEEE International Symposium on Circuits and Systems. Circuits and Systems Connecting the World. ISCAS 96.

[6]  M. A. Melgarejo,et al.  Modified center average defuzzifier for improving the inverted pendulum dynamics , 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

[7]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[8]  Hans-Heinrich Bothe Fuzzy Logic: Einfuhrung in Theorie Und Anwendungen , 1993 .

[9]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[10]  George Boole,et al.  An Investigation of the Laws of Thought: Frontmatter , 2009 .

[11]  W. Ameling,et al.  of the 23 rd Annual EMBS International Conference , October 25-28 , Istanbul , Turkey SCALAR FUZZY LOGIC A NEW MATHEMATIC MODEL FOR APPROXIMATE REASONING , 2004 .

[12]  H. Prade,et al.  Possibilistic logic , 1994 .

[13]  Reiner Hähnle,et al.  Deduction in many-valued logics: a survey , 1997 .

[14]  J. A. Goguen,et al.  The logic of inexact concepts , 1969, Synthese.

[15]  Liliane Peters,et al.  Design and application of an analog fuzzy logic controller , 1996, IEEE Trans. Fuzzy Syst..

[16]  W. Ameling,et al.  Using scalar fuzzy control for aggregation problems in knowledge based diagnosis for implantable devices , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[17]  M. Grabisch Fuzzy integral in multicriteria decision making , 1995 .

[18]  Christian Eitzinger,et al.  Triangular Norms , 2001, Künstliche Intell..

[19]  Chih-Min Lin,et al.  Hierarchical fuzzy sliding-mode control , 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

[20]  Francesc Esteva,et al.  Review of Triangular norms by E. P. Klement, R. Mesiar and E. Pap. Kluwer Academic Publishers , 2003 .

[21]  Edwin Hsing-Mean Sha,et al.  Rapid prototyping for fuzzy systems , 1996, Proceedings of the Sixth Great Lakes Symposium on VLSI.

[22]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decisionmaking , 1988, IEEE Trans. Syst. Man Cybern..

[23]  Hans-Jürgen Zimmermann,et al.  Fuzzy Set Theory - and Its Applications , 1985 .

[24]  Anca L. Ralescu,et al.  Extensions of fuzzy aggregation , 1997, Fuzzy Sets Syst..

[25]  Da Ruan A critical study of widely used fuzzy implication operators and their influence on the inference rules in fuzzy expert systems , 1990 .

[26]  Feijun Song,et al.  A Takagi-Sugeno type fuzzy logic controller with only 3 rules for a 4 dimensional inverted pendulum system , 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.