IOT based Speed Control with Hybrid Neural Fuzzy Logic Scheme

Abstract

 The core idea of this work is to control the speed of the DC shunt motor by conventional laboratory method and adaptive neuro-fuzzy based methods. Armature and Field control are the two conventional methods to control the speed of the DC shunt motor. Presently, Manual speed control is practiced in Electrical Machines laboratory. Through this method it is inferred that the speed is directly proportional to the armature voltage for Armature control scheme and it is inversely proportional to shunt field current in Flux control scheme. This empirical relation stated is validated through the experimental results obtained on laboratory scale in comparison with Hybrid Neural Fuzzy Logic Scheme (HNFLS). This scheme, proposed is equipped with hi-tech arrangement so that the experimentation results can be retrieved from the cloud service in coordination, so that the speed is monitored and controlled online by Internet of Things (IoT).