Using a controller is necessary for any automation system. The controller must be cheap, reliable, user friendly and not cause any problems for inputs and outputs. Classical control systems like proportional integral derivative (PID) put adequate results of linear systems and continuous-time. In fact, real control systems are time-variant, with non-linearity and poorly calculated dynamic variables. For this reason, conventional control systems need an expert person to adjust controller parameters in general. Sometimes an operator is required to solve control problems. Human control is not completely reliable. Also, it does not include any electronic communication. In modern factories, every point must be monitored and electronically controlled from remote points when necessary. In this study, including every electronic communication channel, a simplified handling, low-cost, reliable, Fuzzy Neural Network Controller (FNNC) is designed.
Fuzzy neural network-based model reference adaptive inverse control for induction machines
