mCIT app for teaching and learning the estimation and automatic control of DC motors

Abstract

AbstractTopics of automatic control, parameter identification, and state estimation of a direct current (DC) motor are widely included in undergraduate and graduate engineering programs. Traditionally, theoretical classes are accompanied by simulation or experimental laboratory sessions. The simulation techniques usually do not consider essential dynamic behaviors exhibited by physical systems, such as friction and saturation. Meanwhile, the DC servomechanism, computing device, and associated software used for the experiments are usually expensive. These situations may be avoided through mobile learning by using a low‐cost and portable platform controlled by a mobile device. This article proposes a free Android application called Control and Identification Toolbox for motors (mCIT) and a low‐cost portable platform designed to perform real‐time experiments on DC servomechanisms. The portable platform comprises a mobile device with the mCIT app, a DC servomechanism, and an Arduino‐based data acquisition system. The mobile device, which can be a smartphone, performs the computational and user interface tasks. The effectiveness of the mCIT app and platform are evaluated in online, hybrid, and face‐to‐face courses. The results indicate that the proposed mobile technique improves the teaching and learning experience of automatic control and system estimation topics.