Centroid of a type-2 fuzzy set
Information Sciences: an International Journal
Hardware architecture and FPGA implementation of a type-2 fuzzy system
Proceedings of the 14th ACM Great Lakes symposium on VLSI
Black box evolutionary mathematical modeling applied to linear systems: Research Articles
International Journal of Intelligent Systems - Soft Computing for Modeling, Simulation, and Control of Nonlinear Dynamical Systems
Experimental study of intelligent controllers under uncertainty using type-1 and type-2 fuzzy logic
Information Sciences: an International Journal
Building fuzzy inference systems with a new interval type-2 fuzzy logic toolbox
Transactions on computational science I
Type-2 Fuzzy Sets and Systems: An Overview [corrected reprint]
IEEE Computational Intelligence Magazine - Corrected Reprint
Implementing Interval Type-2 Fuzzy Processors [Developmental Tools]
IEEE Computational Intelligence Magazine
IEEE Transactions on Fuzzy Systems
Interval type-2 fuzzy logic systems: theory and design
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Uncertainty bounds and their use in the design of interval type-2 fuzzy logic systems
IEEE Transactions on Fuzzy Systems
A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots
IEEE Transactions on Fuzzy Systems
A novel programmable CMOS fuzzifiers using voltage-to-current converter circuit
Advances in Fuzzy Systems - Special issue on High Performance Fuzzy Systems for Real World Problems
Designing high-performance fuzzy controllers combining IP cores and soft processors
Advances in Fuzzy Systems - Special issue on High Performance Fuzzy Systems for Real World Problems
WLAN cell handoff latency abatement using an FPGA fuzzy logic algorithm implementation
Advances in Fuzzy Systems - Special issue on High Performance Fuzzy Systems for Real World Problems
Speedup of interval type 2 fuzzy logic systems based on GPU for robot navigation
Advances in Fuzzy Systems - Special issue on High Performance Fuzzy Systems for Real World Problems
Overview of Type-2 Fuzzy Logic Systems
International Journal of Fuzzy System Applications
Effects of type reduction algorithms on forecasting accuracy of IT2FLS models
Applied Soft Computing
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The main goal of this paper is to show that interval type-2 fuzzy inference systems (IT2 FIS) can be used in applications that require high speed processing. This is an important issue since the use of IT2 FIS still being controversial for several reasons, one of the most important is related to the resulting shocking increase in computational complexity that type reducers, like the Karnik-Mendel (KM) iterative method, can cause even for small systems. Hence, comparing our results against a typical implementation of a IT2 FIS using a high level language implemented into a computer, we show that using a hardware implementation the the whole IT2 FIS (fuzzification, inference engine, type reducer and defuzzification) last only four clock cycles; a speed up of nearly 225,000 and 450,000 can be obtained for the Spartan 3 and Virtex 5 Field Programmable Gate Arrays (FPGAs), respectively. This proposal is suitable to be implemented in pipeline, so the complete IT2 process can be obtained in just one clock cycle with the consequently gain in speed of 900,000 and 2,400,000 for the aforementioned FPGAs. This paper also shows that the iterative KM method can be efficient if it is adequately implemented using the appropriate combination of hardware and software. Comparative experiments of control surfaces, and time response in the control of a real plant using the IT2 FIS implemented into a computer against the IT2 FIS into an FPGA are shown.