scholarly journals Embedded two level direct adaptive fuzzy controller for DC motor speed control

2018 ◽  
Vol 9 (1) ◽  
pp. 65-75 ◽  
Author(s):  
Ahmad M. Zaki ◽  
Mohammad El-Bardini ◽  
F.A.S. Soliman ◽  
Mohammed Mabrouk Sharaf
Keyword(s):  
Fuzzy Controller ◽  
Speed Control ◽  
Dc Motor ◽  
Motor Speed ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy

Design on Fuzzy Controller of DC Motors Speed Control Based on DSP

2013 ◽  
Vol 722 ◽  
pp. 357-360
Author(s):  
Peng Jie Zhang ◽  
Ji Hong Guo ◽  
Hong Jing Ma ◽  
Hong Ming Ma
Keyword(s):  
Fuzzy Control ◽  
Fuzzy Controller ◽  
Design Procedure ◽  
Speed Control ◽  
Fast Response ◽  
Dc Motor ◽  
Motor Speed ◽  
Control Effect ◽  
Dc Motor Control ◽  
Fuzzy Control Strategy

Aiming at the problems of nonlinearity, time-variant parameters, and uncertainty of system mathematical model in the PID regulator of DC motor control, a fuzzy controller of DC motor speed control based on TMS320LF2407A is designed in this paper, using the fuzzy control strategy to control, and its design procedure is described. The experimental results show that the speed control system of DC motor by using DSP controller and fuzzy control algorithms has a fast response, slight overshot and good stability, and improves the control effect.

scholarly journals PERFORMANCE IMPROVEMENTS OF SEPARATELY EXCITED DC MOTOR USING FUZZY LOGIC CONTROL

2020 ◽  
Vol 6 (2) ◽  
pp. 47-58
Author(s):  
R. Nagarajan ◽  
M. Gokulkannan ◽  
T. Dinesh ◽  
S. Murugesan ◽  
M. Naveenprasanth
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Expert Knowledge ◽  
Speed Control ◽  
Dc Motor ◽  
Fuzzy Rules ◽  
Motor Speed ◽  
Performance Improvements ◽  
Speed Performance

This paper demonstrates the importance of a fuzzy logic controller over conventional method. The performance of the separately excited DC motor is analyzed by using fuzzy logic controller (FLC) in MATLAB/SIMULINK environment. The FLC speed controller is designed based on the expert knowledge of the fuzzy rules system. The proposed DC motor speed control fuzzy rules are designed for fuzzy logic controller. The output response of the system is obtained by using fuzzy logic controller. The designed fuzzy controller for speed control performance is investigated. Significantly reducing the overshoot and shortening the settling time of the speed response of the motor. They validate different control of approaches, the simulation results show improvement in motor efficiency and speed performance.

scholarly journals Speed Control of Seperately Excited DC motor for Electric Vehicles (EVs) By Inverse Model Based Fuzzy Learning Controller

2021 ◽  
Author(s):  
mehmet bulut
Keyword(s):  
Fuzzy Controller ◽  
Expert Knowledge ◽  
Dc Motor ◽  
Inverse Model ◽  
Fuzzy Rules ◽  
System Stability ◽  
Model Learning ◽  
Adaptation Mechanism ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy

The adaptation mechanism, which adjusts the controller coefficients according to the parameter changes in the system, ensures that the controller is adaptable. Fuzzy logic can be used to calculate the gain coefficients of the controller in the system by using the adaptive fuzzy method instead of a traditional algorithm for the adaptation mechanism. Normally, the rules of a fuzzy controller system are derived from the system's internal structure and system behavior using expert knowledge that has experienced the system. However, it is not possible to derive fuzzy rules based on expert human knowledge for all systems in this way. It is necessary to use different methods to derive fuzzy rules in highly variable behavior and nonlinear systems. In this study, an adaptive fuzzy controller design for dc motor was made using a learning-based reference model learning algorithm using fuzzy inverse model; It has been shown that it is applicable for dc motors with the results obtained. Simulation of the designed system was carried out using the Matlab program, and the behavior of the system was investigated by using constant and variable loads. The results showed that it is satisfactory to drive a dc motor with adaptive fuzzy controller in terms of system stability.

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