Intuitionistic, 2-way adaptive fuzzy control

Date

1999-05-15

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

229
views

0
downloads

Our objective in this paper is to develop a 2-way adaptive fuzzy control system that makes use of the intuitionistic fuzzy sets for modeling expert knowledge bearing uncertainty. Adaptive fuzzy control systems are fuzzy logic systems whose rule parameters are automatically adjusted through training. The training of such system was applied until now, to supports of rule propositions with single distribution such that they can be termed 1-way adaptive. In our system, all supports to propositions have interval valued distributions with necessity at the lower bound and possibility at the upper. Uncertainty in expert knowledge determines the width of the interval. Our first level training tunes rule parameters with necessity function values, while the second level training readjusts these parameters so as to minimize uncertainty based on possibility function values.

Subject Keywords

Adaptive fuzzy control, Interval-valued support, Intuitionistic fuzzy sets

URI

https://hdl.handle.net/11511/53486

Conference Name

International Conference on Robotics and Automation (ICRA '99)

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

FUZZY PREDICTION STRATEGIES FOR GENE-ENVIRONMENT NETWORKS - FUZZY REGRESSION ANALYSIS FOR TWO-MODAL REGULATORY SYSTEMS Kropat, Erik; Ozmen, Ayse; Weber, Gerhard Wilhelm; Meyer-Nieberg, Silja; DEFTERLİ, ÖZLEM (2016-04-01) Target-environment networks provide a conceptual framework for the analysis and prediction of complex regulatory systems such as genetic networks, eco-finance networks or sensor-target assignments. These evolving networks consist of two major groups of entities that are interacting by unknown relationships. The structure and dynamics of the hidden regulatory system have to be revealed from uncertain measurement data. In this paper, the concept of fuzzy target-environment networks is introduced and various f...
Reducing inconsistencies in intuitionistic 2-way adaptive fuzzy control systems Gurkan, E; Erkmen, Aydan Müşerref; Erkmen, İsmet (2000-08-30) 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 i...
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 ...
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...
Application of fuzzy expert decision-making system for rock slope block-toppling modeling and assessment: a case study Azarafza, Mohammad; Asghari-Kaljahi, Ebrahim; Ghazifard, Akbar; Akgün, Haluk (2020-07-01) The strategy applied in this study is fuzzy logic based decision-making system to achieve a rapid way to assess block-toppling failure instability in discontinuous rock slopes as justified by kinematic analysis that are applied to real cases. Referring to fuzzy logic based decision-making; the best option was selected from multiple fuzzy variables through performing a comparison and by obtaining the fastest solution for approximation. The expert system offers a capable fuzzy application for engineering judg...

Citation Formats

E. Gurkan, A. M. Erkmen, and İ. Erkmen, “Intuitionistic, 2-way adaptive fuzzy control,” presented at the International Conference on Robotics and Automation (ICRA ’99), DETROIT, MI, 1999, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53486.