scholarly journals Adaptive proportional-integral fuzzy logic controller of electric motor drive

2021 ◽  
Vol 41 (2) ◽  
Author(s):  
Chiheb Ben Regaya ◽  
Fethi Farhani ◽  
Abderrahmen Zaafouri ◽  
Abdelkader Chaari
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Field Vector ◽  
Motor Drive ◽  
Proportional Integral ◽  
Speed Controller ◽  
Logic Control ◽  
Rotor Resistance ◽  
Resistance Variation ◽  
Electric Motor Drive

This paper presents the indirect field vector control of induction motor (IM) which is controlled by an adaptive Proportional-Integral (PI) speed controller. The proposed solution can overcome the rotor resistance variation, which degrades the performance of speed control. To solve this drawback, an adaptive PI controller is designed with gains adaptation based on fuzzy logic in order to improve the performances of IM with respect to parameters variations, particularly the rotor resistance (Rr). The proposed control algorithm is validated by simulation tests. The obtained results show the robustness towards the load torque disturbances and rotor resistance variation of the adaptive Proportional-Integral fuzzy logic control with respect to classical PI control, and adaptive control based on rotor resistance observer.

scholarly journals Comparison between Fuzzy Logic and PI Control for The Speed Of BLDC Motor

2018 ◽  
Vol 9 (3) ◽  
pp. 1116 ◽  
Author(s):  
Akram H. Ahmed ◽  
Abd El Samie B. Kotb ◽  
Ayman M. Ali
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dynamic Performance ◽  
Bldc Motor ◽  
Motor Speed ◽  
Proportional Integral ◽  
Brushless Dc ◽  
Speed Controller ◽  
Torque Response ◽  
High Degree

In this paper the analytical comparison of brushless DC (BLDC) motor drive with proportional integral (PI) and fuzzy logic controller (FLC) based speed controllers is estimated. Proportional integral (PI) has disadvantages like it do not operate properly when the system has a high degree of load disturbances.<em> </em>In recent years, the application of fuzzy logic controller (FLC) for high dynamic performance of motor drives has become an important tool. FLC is a good for load disturbances and can be easily implemented. The modeling and simulation of both the speed controllers have been made by MATLAB/SIMULINK. The dynamic characteristics of the BLDC motor (speed and torque) response, obtained under PI and Fuzzy logic based speed controller, are compared for various operating condition.

Fuzzy Logic Based Speed Control of an IPM Synchronous Motor Drive

2000 ◽  
Vol 4 (3) ◽  
pp. 212-219 ◽  
Author(s):  
M. N. Uddin ◽  
◽  
M. A. Rahman
Keyword(s):  
Fuzzy Logic ◽  
Permanent Magnet ◽  
Fuzzy Logic Controller ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Operating Conditions ◽  
Motor Drive ◽  
Speed Controller ◽  
Synchronous Motor Drive ◽  
Interior Permanent Magnet

This paper presents the on-line implementation of a novel fuzzy logic based speed controller for an interior permanent magnet synchronous motor drive. The fundamentals of fuzzy logic algorithms relating to motor control applications are illustrated. A new fuzzy speed controller for the IPMSM drive is designed. The complete vector control scheme incorporating the fuzzy logic controller (FLC) is successfully implemented in real-time using a digital signal processor board DS 1102 in a laboratory 1 hp interior permanent magnet synchronous motor (IPMSM). The efficacy of the proposed fuzzy logic controller (FLC) based IPMSM drive is verified by simulation as well as experimental results at different dynamic operating conditions. The fuzzy logic controller is found to be more robust for application in the IPMSM drive.

A contribution to the identification in fuzzy-logic control

1990 ◽  
Vol 55 (4) ◽  
pp. 951-963 ◽  
Author(s):  
Josef Vrba ◽  
Ywetta Purová
Keyword(s):  
Time Series ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Automatic Generation ◽  
Linguistic Variable ◽  
Fuzzy Subset ◽  
Input Output ◽  
Logic Control ◽  
Correlation Tables

A linguistic identification of a system controlled by a fuzzy-logic controller is presented. The information about the behaviour of the system, concentrated in time-series, is analyzed from the point of its description by linguistic variable and fuzzy subset as its quantifier. The partial input/output relation and its strength is expressed by a sort of correlation tables and coefficients. The principles of automatic generation of model statements are presented as well.

scholarly journals Exhaust Fan Speed Controller Using Fuzzy Logic Controller

2021 ◽  
Vol 1737 (1) ◽  
pp. 012046
Author(s):  
M Khairudin ◽  
Sigit Yatmono ◽  
Irdayanti M Nashir ◽  
Fatchul Arifin ◽  
W Aulia ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Speed Controller ◽  
Fan Speed

Comparison of a Fuzzy Logic Controller With a P + D Control Law

1989 ◽  
Vol 111 (2) ◽  
pp. 128-137 ◽  
Author(s):  
S. Daley ◽  
K. F. Gill
Keyword(s):  
Fuzzy Logic ◽  
Attitude Control ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Good Control ◽  
Control Law ◽  
Dynamic Coupling ◽  
Process Knowledge ◽  
Logic Control ◽  
Limited Process

A study is described that compares the performance of a self-organizing fuzzy logic control law (SOC) with that of the more traditional P + D algorithm. The multivariate problem used for the investigation is the attitude control of a flexible satellite that has significant dynamic coupling of the axes. It is demonstrated that the SOC can provide good control, requires limited process knowledge and compares favorably with the P + D algorithm.

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