Reference Model Based Adaptive Fuzzy Controller for Direct Current Motor Drive Using Fuzzy Inverse Model

Year 2023, Volume: 26 Issue: 2, 593 - 602, 05.07.2023

Mehmet Bulut

https://doi.org/10.2339/politeknik.877909

Cited By: 2

Abstract

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.

Keywords

Fuzzy control, rule base, reference model, DC Motor, adaptive controller

Bulanık Ters Model Kullanılarak Doğru Akım Motor Sürücüsü için Referans Model Temelli Uyarlanabilir Bulanık Denetleyici

Abstract

Sistemdeki parametre değişimlerine göre denetleyici katsayılarını ayarlayan uyarlama mekanizması, denetleyicinin uyarlanabilir olmasını sağlamaktadır. Uyarlama mekanizması için geleneksel bir algoritma yerine uyarlanabilir bulanık metodu kullanılarak, sistemdeki denetleyicinin kazanç katsayıların hesaplanması için bulanık mantık kullanılabilir. Normalde bir bulanık denetleyici sistemine ait kurallar, sistemi deneyimlemiş olan uzman bilgisi kullanılarak sistemin içyapısından ve sistem davranışlarından çıkarılmaktadır. Ancak tüm sistemler için bu şekilde uzman insan bilgisine dayanan bulanık kuralların çıkarılması mümkün değildir. Çok değişken davranış gösteren ve doğrusal olmayan sistemlerde bulanık kurallarının çıkarılması için farklı yöntemlerin kullanılması ihtiyacı ortaya çıkmaktadır. Bu çalışmada, bulanık ters model kullanılarak öğrenmeye dayalı referans model öğrenme algoritması kullanılarak dc motor için uyarlanabilir bulanık denetleyici tasarımı yapılmış; elde edilen sonuçlar ile dc motor için uygulanabilir olduğu gösterilmiştir. Tasarlanan sistemin benzetimi Matlab programı kullanılarak gerçekleştirilmiş, sabit ve değişken yükler kullanılarak sistemin davranışı incelenmiştir. Elde edilen sonuçlar, sistem kararlılığı açısından uyarlanabilir bulanık denetleyici ile dc motoru sürmek için tatmin edici olduğunu göstermiştir.

Keywords

Bulanık denetleyici, kural taban, referans model, DA motoru, uyarlanabilir denetleyici

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