FPGA based real-time adaptive fuzzy logic controller

2010 ◽  
Author(s):  
Aws Abu-Khudhair ◽  
Radu Muresan ◽  
Simon X. Yang
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Fuzzy Logic Controller ◽  
Adaptive Fuzzy ◽  
Adaptive Fuzzy Logic

scholarly journals Innovative Strategy to Improve Precision and to Save Power of a Real-Time Control Process Using an Online Adaptive Fuzzy Logic Controller

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
R. Lasri ◽  
I. Rojas ◽  
H. Pomares ◽  
O. Valenzuela
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Fuzzy Logic Controller ◽  
Control Process ◽  
Control Area ◽  
Real Time Control ◽  
Innovative Strategy ◽  
Adaptive Fuzzy ◽  
Time Control ◽  
Adaptive Fuzzy Logic

The main objective of this paper is to prove the great advantage that brings our novel approach to the intelligent control area. A set of various types of intelligent controllers have been designed to control the temperature of a room in a real-time control process in order to compare the obtained results with each other. Through a training board that allows us to control the temperature, all the used algorithms should present their best performances in this control process; therefore, our self-organized and online adaptive fuzzy logic controller (FLC) will be required to present great improvements in the control task and a real high control performance. Simulation results can show clearly that the new approach presented and tested in this work is very efficient. Thus, our adaptive and self-organizing FLC presents the best accuracy compared with the remaining used controllers, and, besides that, it can guarantee an important reduction of the power consumption during the control process.

Adaptive fuzzy logic controller for DC–DC converters

2009 ◽  
Vol 36 (2) ◽  
pp. 1540-1548 ◽  
Author(s):  
Cetin Elmas ◽  
Omer Deperlioglu ◽  
Hasan Huseyin Sayan
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Adaptive Fuzzy ◽  
Adaptive Fuzzy Logic

Self Tuning Based Adaptive Fuzzy Logic Controller in Lab view for Sterilizing Equipments

2014 ◽  
Vol 3 (2) ◽  
pp. 84
Author(s):  
P. J. Ragu
Keyword(s):  
Fuzzy Logic ◽  
Temperature Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Lab View ◽  
Adaptive Fuzzy Logic ◽  
Self Tuning ◽  
Input Variables ◽  
Temperature Errors

In this paper, temperature monitoring of sterilizing equipment system was established with the help of fuzzy and self tuning Adaptive fuzzy logic controller designed in Lab VIEW software. It combines the advantages of both fuzzy logic and self tuning Adaptive fuzzy logic controller. The implementation attempts to rectify the errors between the measured value and the set point which helps to achieve efficient temperature control. The Adaptive fuzzy controller uses defined rules to control the system based on the current values of input variables and temperature errors. The simulation results presented in order to evaluate the proposed method. The result shows that self tuning  Adaptive fuzzy logic controller was tolerant to disturbance and the temperature control is most accurate.

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