Control and optimization of DC motor using perceptron algorithm to increase efficiency

DC motors have different speeds and are easier to control. Mostly DC motor speeds are controlled by armature voltage or field control. The control methods presented for DC motors have been expanded with the introduction of new methods in control theory. In this paper, the speed of a DC series motor is controlled using a linear adaptive neural network. The effect of the load and voltage changes of the armature is considered in this controller. The characteristic of the proposed method is the modification of the neural network coefficients while the engine is running and the responses are resistant to changes.