DSP Based Fuzzy-Neural Speed Tracking Control of Brushless DC Motor

Gençer, Çetin; Saygin, Ali; Coşkun, İsmail

doi:10.1007/11803089_13

Cited by 4 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The stability analysis method based on the higher ordered derivatives of universal learning networks and its application to a DC motor system were described [19][20][21]. Fuzzy-Neuro control architecture was applied for some special electrical machines like brush less DC motor, permanent magnet DC motor and switched reluctance motor in order to obtain the precise speed control and better performances [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis and Experimental Verification of Buck Converter fed DC Series Motor using Hybrid Intelligent Controller with Stability Analysis and Parameter Variations

Thangaraju¹,

Muruganandam²,

Madheswaran³

2015

Journal of Electrical Engineering and Technology

View full text Add to dashboard Cite

-This article presents a closed loop control of DC series motor fed by DC chopper controlled by an PID controller based intelligent control using ANN (Artificial Neural Network). The PID-ANN controller performances are analyzed in both steady state and dynamic operating condition with various set speed and various load torque. Here two different motor parameters are taken for analysis (220V and 110V motor parameters). The static and dynamic performances are taken for comparison with conventional PID controller and existing work. The steady state stability analysis of the system also made using the transfer function model. The equation model is also done to analysis the performances by set speed change and load torque change. The proposed controller have better control over the conventional PID controller and the reported existing work. This system is initially simulated using MATLAB / Simulink and then experimental setup done using P89V51RD2BN microcontroller.

show abstract