Abstract: In this study, a three-phase bridge controlled rectifier is used to drive and control a Separately Excited DC Motor (SEDCM) at desired values depending on different intelligent controllers, which are trained to get the desired values of firing angles to trig thyristors. The Fuzzy Logic (FL), FL with bacterial foraging algorithm (FL-BFA), BFA with PI (PI-BFA), artificial neural network with PI (ANN-PI), PI and Neurofuzzy (NFC) controllers are used and adopted to control speed of the SEDCM. Responses of the DC motor speed and torque are estimated using its transfer function characteristics and instantaneous output voltage and current of the controlled converter. The AC/DC drive circuit with intelligent controllers is adopted and modeled under different values of speed and torque conditions in stable and dynamic conditions. Model results explained success of the designed controller system. Also, it showed that during reducing speed, the FL, FL-BFA and NFC techniques caused the SEDCM to run out of working range. Therefore, PI-BFA, ANN-PI and PI techniques are dependable controllers and gave almost the same speed and torque responses. But the PI-BFA is considered the best. The speed and torque responses have acceptable agreement between the actual, estimated and desired values with fast dynamic response.
Nashwan Saleh Sultan, Rakan Khalil Antar and Bashar Abbas Fadheel, 2018. A Comparative Control Study of a Separately Excited DC Motor Using Intelligent Controllers. Journal of Engineering and Applied Sciences, 13: 9800-9806.