A neuro-PID speed controller for DC drives

In this paper, a hybrid controller, consisting of a conventional proportional-integral-derivative (PID) controller and a neurocontroller, is proposed. This controller combines the learning capabilities of artificial neural network-based controllers and the global asymptotic stability of conventional PID controllers to control a DC motor. This kind of controller provides better control of nonlinear plant which otherwise would have been difficult to control without the proper tuning of PID gains. Simulation results are presented for the speed control of a DC motor.