Tolerating failures of continuous-valued sensors
ACM Transactions on Computer Systems (TOCS)
Non-specificity and interval-valued fuzzy sets
Fuzzy Sets and Systems
An ACS Robotic Control Algorithm with Fault Tolerant Capabilities
FCCM '00 Proceedings of the 2000 IEEE Symposium on Field-Programmable Custom Computing Machines
Arithmetic operators in interval-valued fuzzy set theory
Information Sciences: an International Journal
Uncertainty measures for interval type-2 fuzzy sets
Information Sciences: an International Journal
An efficient centroid type-reduction strategy for general type-2 fuzzy logic system
Information Sciences: an International Journal
The collapsing method of defuzzification for discretised interval type-2 fuzzy sets
Information Sciences: an International Journal
Interval type-2 fuzzy membership function generation methods for pattern recognition
Information Sciences: an International Journal
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
IEEE Transactions on Fuzzy Systems
Enhanced Karnik-Mendel algorithms
IEEE Transactions on Fuzzy Systems
α-plane representation for type-2 fuzzy sets: theory and applications
IEEE Transactions on Fuzzy Systems
Toward general type-2 fuzzy logic systems based on zSlices
IEEE Transactions on Fuzzy Systems
Uncertainty measures for general Type-2 fuzzy sets
Information Sciences: an International Journal
On the robustness of Type-1 and Interval Type-2 fuzzy logic systems in modeling
Information Sciences: an International Journal
IEEE Transactions on Fuzzy Systems
"Fuzzy" versus "nonfuzzy" in combining classifiers designed by Boosting
IEEE Transactions on Fuzzy Systems
A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots
IEEE Transactions on Fuzzy Systems
Interval Type-2 Fuzzy Logic Systems Made Simple
IEEE Transactions on Fuzzy Systems
Geometric Type-1 and Type-2 Fuzzy Logic Systems
IEEE Transactions on Fuzzy Systems
A Consensus Model for Group Decision Making With Incomplete Fuzzy Preference Relations
IEEE Transactions on Fuzzy Systems
Robustness of interval-valued fuzzy inference
Information Sciences: an International Journal
The sampling method of defuzzification for type-2 fuzzy sets: Experimental evaluation
Information Sciences: an International Journal
A survey-based type-2 fuzzy logic system for energy management in hybrid electrical vehicles
Information Sciences: an International Journal
Information Sciences: an International Journal
Algebraic structures of interval-valued fuzzy ( S,N)-implications
International Journal of Approximate Reasoning
Complete solution sets of inf → interval-valued fuzzy relation equations
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
A closed form type reduction method for piecewise linear interval type-2 fuzzy sets
International Journal of Approximate Reasoning
Information Sciences: an International Journal
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A voting scheme constitutes an essential component of many fault tolerant systems. Two types of voters are commonly used in applications of real-valued systems: the inexact majority and the amalgamating voters. The inexact majority voter effectively isolates erroneous modules and is capable of reporting benign outputs when a significant disagreement is detected. However, an application specific voter threshold must be provided. On the other hand, amalgamating voter, such as the weighted average voter, reduces the influence of faulty modules by averaging the input values together. Unlike the majority voters, amalgamating voters are not capable of producing benign outputs. In the past, a Type-1 (T1) fuzzy voting scheme was introduced, allowing for both smooth amalgamation of voter inputs and effective signalization of benign outputs. The presented paper proposes an extension to the fuzzy voting scheme via incorporating Interval Type-2 (IT2) fuzzy logic. The IT2 fuzzy logic allows for an improved handling of uncertain assumptions about the distributions of noisy and erroneous inputs which are essential for correct design of the fuzzy voting scheme. The proposed voter design features robust performance when the uncertainty assumptions dynamically change over time. The IT2 fuzzy voter architecture was compared against the average voter, inexact majority voter, and the T1 fuzzy voter using a refined experimental harness. The reported results demonstrate improved availability, safety and reliability of the presented IT2 fuzzy voting scheme.