Speed control of DC motor using PID controller based on artificial intelligence techniques

The aim of this paper is to design a speed controller of a DC motor by selection of a PID parameters using genetic algorithm (GA) and Adaptive Neuro-Fuzzy Inference System (ANFIS). DC motor could be represented by a nonlinear model when nonlinearities such as magnetic saturation are considered. To provide effective control, nonlinearities and uncertainties in the model must be taken into account in the control design. The model of a DC motor is considered as a third order system. And this paper compares three kinds of tuning methods of parameter for PID controller. One is the controller design by the Ziegler and Nichols, second is the controller design by the Genetic Algorithm method and third is the controller design by Adaptive Neuro-Fuzzy Inference System (ANFIS). The proposed methods could be applied to the higher order systems.