scholarly journals Optimal Adjustment of Evolutionary Algorithm-Based Fuzzy Controller for Driving Electric Motor with Computer Interface

2021 ◽  
Vol 21 (3) ◽  
pp. 366-375
Author(s):  
Mehmet Bulut ◽  
Keyword(s):  
Evolutionary Algorithm ◽  
Electric Motor ◽  
Fuzzy Controller ◽  
Computer Interface ◽  
Optimal Adjustment

scholarly journals Optimal Adjustment of Evolutionary Algorithm-Based Fuzzy Controller for Driving Electric Motor with Computer Interface

2021 ◽  
Author(s):  
mehmet bulut
Keyword(s):  
Evolutionary Algorithm ◽  
Electric Motor ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Computer Interface ◽  
Rule Base ◽  
Learning Stage ◽  
Interface Circuit ◽  
Termination Criteria ◽  
Optimal Adjustment

This study focused on the development of a system based on evolutionary Algorithms to obtain the optimum parameters of the fuzzy controller to increase the convergence speed and accuracy of the controller. The aim of the study is to design fuzzy controller without expert’s knowledge by using evolutionary genetic algorithms and carry out on a DC motor. The design is based on optimization of rule bases of fuzzy controller. In the learning stage, the obtained rule base fitness values are measured by working the rule base on the controller. The learning stage is repeated the termination criteria. The proposed fuzzy controller is performed on the dc motor from a PC program using a interface circuit.<div>Note : This article has been accepted for publication in a future issue of ELECTRICA journal, it is now in the early view. </div><div>Citation information: </div><div>M. Bulut, "Optimal Adjustment of Evolutionary Algorithm-based Fuzzy Controller for Driving Electric Motor with Computer Interface", Electrica, August 5, 2021. DOI: 10.5152/electrica.2021.21033.</div>

scholarly journals Optimal Adjustment of Fuzzy Controller Based Evolutionary Algorithms For Driving Electric Motor with Computer Interface

2020 ◽  
Author(s):  
mehmet bulut
Keyword(s):  
Evolutionary Algorithms ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Rule Base ◽  
Learning Stage ◽  
Interface Circuit ◽  
Termination Criteria ◽  
Optimum Parameters ◽  
Optimal Adjustment ◽  
Rule Bases

This study focused on the development of a system based on evolutionary Algorithms to obtain the optimum parameters of the fuzzy controller to increase the convergence speed and accuracy of the controller. The aim of the study is to design fuzzy controller without expert’s knowledge by using evolutionary genetic algorithms and carry out on a DC motor. The design is based on optimization of rule bases of fuzzy controller. In the learning stage, the obtained rule base fitness values are measured by working the rule base on the controller. The learning stage is repeated the termination criteria. The proposed fuzzy controller is performed on the dc motor from a PC program using a interface circuit.

scholarly journals Optimal Adjustment of Fuzzy Controller Based Evolutionary Algorithms For Driving Electric Motor with Computer Interface

2020 ◽  
Author(s):  
mehmet bulut
Keyword(s):  
Evolutionary Algorithms ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Rule Base ◽  
Learning Stage ◽  
Interface Circuit ◽  
Termination Criteria ◽  
Optimum Parameters ◽  
Optimal Adjustment ◽  
Rule Bases

This study focused on the development of a system based on evolutionary Algorithms to obtain the optimum parameters of the fuzzy controller to increase the convergence speed and accuracy of the controller. The aim of the study is to design fuzzy controller without expert’s knowledge by using evolutionary genetic algorithms and carry out on a DC motor. The design is based on optimization of rule bases of fuzzy controller. In the learning stage, the obtained rule base fitness values are measured by working the rule base on the controller. The learning stage is repeated the termination criteria. The proposed fuzzy controller is performed on the dc motor from a PC program using a interface circuit.

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