Parametric regression methodology and optimized control for DC motor

This paper presents a speed control for a DC motor. Despite the unknown parameters of the plant to be controlled, these parameters are found using a system identification method. The methodology implemented in this study is known as parametric regression and is based on an optimization technique. This optimization, through its fitness function, allows to find the system characteristics in order to make possible the system control. This control is applied to the DC motor speed through a cascade PI controller, acting on the motor current. Besides, the controller parameters are found through deterministic optimization technique, using the Quasi-Newton method. Simulation and experimental results are presented in order to validate the study and make possible the control of an unknown parameters system.