scholarly journals Speedup of Interval Type 2 Fuzzy Logic Systems Based on GPU for Robot Navigation

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Long Thanh Ngo ◽  
Dzung Dinh Nguyen ◽  
Long The Pham ◽  
Cuong Manh Luong
Keyword(s):  
Fuzzy Logic ◽  
High Performance ◽  
Graphics Processing Unit ◽  
Robot Navigation ◽  
Processing Unit ◽  
Fuzzy Logic Systems ◽  
Logic Systems ◽  
Membership Value ◽  
Interval Type

As the number of rules and sample rate for type 2 fuzzy logic systems (T2FLSs) increases, the speed of calculations becomes a problem. The T2FLS has a large membership value of inherent algorithmic parallelism that modern CPU architectures do not exploit. In the T2FLS, many rules and algorithms can be speedup on a graphics processing unit (GPU) as long as the majority of computation a various stages and components are not dependent on each other. This paper demonstrates how to install interval type 2 fuzzy logic systems (IT2-FLSs) on the GPU and experiments for obstacle avoidance behavior of robot navigation. GPU-based calculations are high-performance solution and free up the CPU. The experimental results show that the performance of the GPU is many times faster than CPU.

Design of back propagation optimized Nagar-Bardini structure-based interval type-2 fuzzy logic systems for fuzzy identification

2021 ◽  
pp. 014233122110066
Author(s):  
Yang Chen ◽  
Jiaxiu Yang
Keyword(s):  
Fuzzy Logic ◽  
Back Propagation ◽  
Membership Functions ◽  
Identification Problems ◽  
Fuzzy Logic Systems ◽  
Fuzzy Identification ◽  
Logic Systems ◽  
Academic Topic ◽  
Interval Type

In recent years, fuzzy identification based on system identification theory has become a hot academic topic. Interval type-2 fuzzy logic systems (IT2 FLSs) have become a rising technology. This paper designs a type of Nagar-Bardini (NB) structure-based singleton IT2 FLSs for fuzzy identification problems. The antecedents of primary membership functions of IT2 FLSs are chosen as Gaussian type-2 primary membership functions with uncertain standard deviations. Then, the back propagation algorithms are used to tune the parameters of IT2 FLSs according to the chain rule of derivation. Compared with the type-1 fuzzy logic systems, simulation studies show that the proposed IT2 FLSs can obtain better abilities of generalization for fuzzy identification problems.

Application of Interval Type-2 Fuzzy Logic Systems for Control of the Coiling Entry Temperature in a Hot Strip Mill

2009 ◽  
pp. 352-359 ◽  
Author(s):  
Gerardo M. Méndez ◽  
Luis Leduc-Lezama ◽  
Rafael Colas ◽  
Gabriel Murillo-Pérez ◽  
Jorge Ramírez-Cuellar ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Hot Strip Mill ◽  
Fuzzy Logic Systems ◽  
Hot Strip ◽  
Logic Systems ◽  
Interval Type
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