Type-2 Fuzzy Logic Control of Trade-off between Exploration and Exploitation Properties of Genetic Algorithms

2012 ◽  
pp. 368-376 ◽  
Author(s):  
Adam Slowik
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Exploration And Exploitation ◽  
Trade Off ◽  
Logic Control

scholarly journals INTERVAL TYPE-2 FUZZY LOGIC CONTROL FOR THE MULTIVARIABLE ANAESTHESIA SYSTEM

2010 ◽  
Vol 38 (6) ◽  
pp. 1485-1506
Author(s):  
Mohammad El-Bardini ◽  
Ahmad M. El-Nagar ◽  
Nabila M. El-Rabaie
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Logic Control ◽  
Interval Type

Type-2 fuzzy logic control of a photovoltaic sourced two stages converter

2018 ◽  
Vol 35 (1) ◽  
pp. 1103-1117 ◽  
Author(s):  
Omer Faruk Bay ◽  
Meral Ozarslan Yatak
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Logic Control ◽  
Two Stages

Genetic Algorithms Optimized Fuzzy Logic Control to Support the Generation of Lightning Warnings

2013 ◽  
Vol 25 (1) ◽  
pp. 32-45 ◽  
Author(s):  
Adriel Y. S. Igarashi ◽  
Gideon V. Leandro ◽  
Gustavo H. C. Oliveira ◽  
Eduardo A. Leite
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Logic Control

Interval Type-2 Fuzzy Logic Control of NM70 Shape Memory Actuator

2014 ◽  
Author(s):  
Ireneusz Dominik
Keyword(s):  
Fuzzy Logic ◽  
Shape Memory ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Logic Control ◽  
Interval Type ◽  
Nonlinear Plant

The main aim of this article is to present the usage of type-2 fuzzy logic controller to control a shape memory actuator. To enhance real-time performance simplified interval fuzzy sets were used. The algorithm was implemented in the ATmega32 microcontroller. The dedicated PC application was also built. The fuzzy logic controller type-2 was tested experimentally by controlling position of the shape memory alloy actuator NM70 which despite its small size distinguishes itself by its strength. The obtained results confirmed that type-2 fuzzy controller performed efficiently with a difficult to control nonlinear plant. The research also proved that interval type-2 controllers, which are a simplified version of the general type-2 controllers, are very efficient. They can handle uncertainties without increasing drastically the computational complexity. Experimental data comparison of the fuzzy logic controller type-2 with type-1 clearly indicates the superiority of the former, especially in reducing overshooting.

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