Sensorless position control of DC motor using model predictive controller

Abstract

Sensors like rotary encoders are widely used in measuring the speed and position of DC motor in applications. Due to expensiveness, calibration complexities of these type of encoders, sensorless methods for measurements were used alternatively. This paper presents sensorless position control of a wheeled DC motor using system identified model. This approach overcome some conventional sensorless techniques that uses some approximations. The model is developed using black box identification scheme, based on the identified model, a model predictive controller was designed to track a desired horizontal position of the wheel. Practical experiment shows the concept gives a very good estimation of the position and speed and can be used in control application.