Speed Control of Vector Controlled Induction Motors under Variable Load with RBFNN Based Model Reference Adaptive Control

Abstract

In the speed control of induction motors, an acceptable good performance cannot be obtained by using traditional feedback controllers due to the non-linear structure of the system, the effects of changing environmental conditions and several disturbance inputs. On the other hand, in recent years, it has been demonstrated that artificial intelligence based control methods were much more successful in the nonlinear system control applications. In this study, an intelligent controller has been developed for speed control of induction motors by using radial basis function neural network (RBFNN) and model reference adaptive control (MRAC) strategy. In the driving of induction motor, indirect field oriented vector control method which is widely used in high-performance drive system has been preferred. Simulation results to determine the success of the development of this control method was compared with conventional PI type controller. While the motor is under the fan-type load, the performance of controller has been investigated in Matlab/Simulink environment. The simulation results demonstrate that the performance of RBFNN based MRAC controller is better than that of conventional PI controller.

Keywords

• Radial Basis Function Neural Network, Model Reference Adaptive Control, Induction Motor

Vektör Kontrollü Asenkron Motorların RTYSA Temelli Model Referans Adaptif Kontrol ile Değişken Yük Altında Hız Denetimi

Abstract

Asenkron motorların hız denetiminde, sistemin doğrusal olmayan yapısı, değişen çevre koşulları ve bozucu girişlerin etkisi nedeniyle geleneksel geri beslemeli denetleyiciler ile iyi bir performans elde edilememektedir. Asenkron motor sürücülerinin performansının arttırılmasında yapay zekâ tabanlı yöntemlerin kullanılmasının yararları son yıllardaki araştırmalarla açık bir şekilde ortaya konulmuştur. Bu çalışmada radyal tabanlı yapay sinir ağlarından (RTYSA) ve model referans adaptif kontrol (MRAK) yapısından faydalanılarak asenkron motorların hız denetimi için yapay zekâ esaslı bir denetleyici geliştirilmiştir. Asenkron motorun sürme yönteminde, yüksek performanslı sürücü sistemlerinde yaygın olarak kullanılan dolaylı alan yönlendirmeli vektör kontrol tekniği tercih edilmiştir. Geliştirilen bu denetim yönteminin başarısını belirlemek amacıyla benzetim sonuçları geleneksel PI-tipi denetleyici ile karşılaştırılmıştır. Motor fan tipi yük altında iken, denetleyicinin performansı Matlab/Simulink ortamında incelenmiştir. Simülasyon sonuçları RTYSA temelli MRAK denetleyici performansının, geleneksel PI denetleyiciden daha iyi olduğunu göstermiştir.

Keywords

• Radyal Tabanlı Yapay Sinir Ağları, Model Referans Adaptif Kontrol, Asenkron Motor

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