A Modular Implementation Scheme for Nonsingleton Type-2 Fuzzy Logic Systems With Input Uncertainties

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Using nonsingleton (NS) input fuzzifiers along with type-2 fuzzy systems to handle uncertainties in inputs has received some attention in recent years. However, the NS fuzzification schemes proposed so far have a limited impact because they are restricted to a particular kind of fuzzy sets only. This paper proposes a modular implementation scheme for NS type-2 fuzzy logic systems with input uncertainties. The proposed implementation scheme constitutes a generalized fuzzification which is independent of the forms/shapes of the fuzzy sets, i.e., both the NS fuzzifiers and the membership functions. To investigate the effectiveness of the proposed scheme, type-2 fuzzy logic controllers for three different applications, airplane altitude control, obstacle avoidance for a mobile robot, and a wall following robot, are developed. Additionally, for mapping NS fuzzifiers for real sensors, a sensory noise pattern recognition stage is also developed. Despite encountering various kinds of membership functions and input uncertainties along these three applications, the proposed scheme is able to successfully deal with all three applications. Moreover, the performance results in all three application setups show that NS fuzzification can improve the robustness of type-2 fuzzy logic systems against input uncertainties.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2015-12
Language
English
Article Type
Article
Keywords

REAL-WORLD APPLICATIONS; ROBOT; DESIGN; MODELS

Citation

IEEE-ASME TRANSACTIONS ON MECHATRONICS, v.20, no.6, pp.3182 - 3193

ISSN
1083-4435
DOI
10.1109/TMECH.2015.2411853
URI
http://hdl.handle.net/10203/205148
Appears in Collection
EE-Journal Papers(저널논문)
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