Reducing inconsistencies in intuitionistic 2-way adaptive fuzzy control systems

Date

2000-08-30

Author

Gurkan, E
Erkmen, Aydan Müşerref
Erkmen, İsmet

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

59
views

0
downloads

Our objective in this paper is to model and reduce inconsistency in expert knowledge for our proposed 2-way adaptive fuzzy system that makes use of intuitionistic fuzzy sets. Intuitionistic fuzzy sets model an interval valued distribution of information in the adaptive control architecture with the necessity at the lower bound as the degree of membership functions and the possibility at the upper bound as the complement of the degree of nonmembership functions. Uncertainty is modelled as the width of this interval. A width of zero is at the basis of a deterministic control. The use of intuitionistic fuzzy sets brings a flexibility in the system since it is possible to assign control upper bounds (nonmembership functions) independently from control lower bounds (the membership functions). There is only a consistency constraint on this assignment, which is that the sum of the two functions should be less than or equal to unity. However, in many control problems, this inequality constraint is not satisfied giving rise to inconsistency. The proposed 2-way adaptive fuzzy system is subject to training for the adjustment of parameters. The training of adaptive fuzzy systems was originally applied to supports of rule propositions with single distribution such that they can be termed 1-way adaptive. The novelty in our approach is due to the additional training required for the adjustment of the parameters of the nonmembership functions. Moreover, our proposed system is subject to two phases of training. The first phase of training is necessary in order to obtain a consistent 2-way adaptive fuzzy control system by reducing optimally any inherent inconsistencies. The purpose of the second phase is to reduce the uncertainty defined as the width introduced by the independent assignments of membership and nonmembership functions. The resultant system is a one-way fuzzy adaptive system without inconsistency and without uncertainty.

Subject Keywords

SETS

URI

https://hdl.handle.net/11511/37175

DOI

https://doi.org/10.1142/9789812792631_0035

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Evaluation of inconsistency in a 2-way fuzzy adaptive system using shadowed sets Gurkan, E; Erkmen, Aydan Müşerref; Erkmen, İsmet (2001-05-24) Our objective in this paper is to evaluate inconsistency for our proposed 2-way fuzzy adaptive system that makes use of intuitionistic fuzzy sets. Uncertainty is modeled as the width of the interval introduced by the independent assignment of membership and nonmembership functions of the intuitionistic fuzzy sets. There is only a consistency constraint in this assignment, violation of which gives rise to inconsistency in the system. The inconsistency model using this fact is reduced through training. There ...
The enhancement of the cell-based GIS analyses with fuzzy processing capabilities Yanar, Tahsin Alp; Akyürek, Sevda Zuhal; Department of Geodetic and Geographical Information Technologies (2003) In order to store and process natural phenomena in Geographic Information Systems (GIS) it is necessary to model the real world to form computational representation. Since classical set theory is used in conventional GIS software systems to model uncertain real world, the natural variability in the environmental phenomena can not be modeled appropriately. Because, pervasive imprecision of the real world is unavoidably reduced to artificially precise spatial entities when the conventional crisp logic is used...
Two-way fuzzy adaptive identification and control of a flexible-joint robot arm Gurkan, E; Erkmen, İsmet; Erkmen, Aydan Müşerref (2002-08-01) The objective in this paper is to apply our proposed two-way fuzzy adaptive system that makes use of intuitionistic fuzzy sets to the identification and model-based control of a flexible-joint robot arm. Uncertainty and inconsistency are modelled in the proposed system such as uncertainty is the width of the interval introduced by the independent assignment of membership and nonmembership functions of the intuitionistic fuzzy sets; and inconsistency is the violation of the consistency inequality in this ass...
Genetically tuned fuzzy scheduling for flexible manufacturing systems. Erkmen, Aydan Müşerref; Anlagan, O; Unver, O (1997-04-25) This paper focuses on the development and implementation of a Genetically Tuned Fuzzy Scheduler (GTFS) for heterogeneous FMS under uncertainty. The scheduling system takes input from a table and creates an optimum master schedule. The GTFS uses fuzzy rulebase and inferencing where fuzzy sets are generated by a genetic algorithm to tune the optimization. The fuzzy optimization is based on time criticality in deadline and machine need, taking into account machine availability, uniformity, process time and sel...
Handling complex and uncertain information in the ExIFO and NF2 data models Yazıcı, Adnan; Petry, FE (1999-12-01) Trends in databases leading to complex objects present opportunities for representing imprecision and uncertainty that were difficult to integrate cohesively in simpler database models. In fact, one can begin at the conceptual level with a model that allows uncertainty assumptions and then transform those assumptions into a logical model having the necessary semantic foundations upon which to base a meaningful query language. Here we provide such a constructive approach beginning with the ExIFO model for ex...

Citation Formats

E. Gurkan, A. M. Erkmen, and İ. Erkmen, “Reducing inconsistencies in intuitionistic 2-way adaptive fuzzy control systems,” 2000, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/37175.