Control and Identification Toolbox (CIT): An Android application for teaching automatic control and system identification

Abstract

This article presents a free Android application, named as Control and Identification Toolbox (CIT), for teaching and learning the system response, automatic control, and the parameter identification of dynamic systems. The CIT app performs real-time experiments and permits tuning a traditional proportional-integral-derivative controller, whose performance under constant or noise disturbances, introduced by the app, can be analyzed. Moreover, this app allows estimating the parameters of first-and second-order linear systems by means of the recursive least squares method. The parameter estimates as well as the control system signals produced under common test input signals are displayed by the app. It runs in any Android device supporting a universal serial bus, which is connected with Arduino Uno or Mega boards that carry out data acquisition. Experimental results obtained using first-and second-order low-pass filters confirm the effectiveness of the proposed application. Moreover, undergraduate students evaluated the CIT app, and their responses are also presented. K E Y W O R D S

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

“…The main characteristics of the mCIT app are similar to those of the CIT app reported by Concha et al [9]. For example, the mCIT app includes the class files utilized in the CIT app.…”

“…rev, respectively. For this experiment, the motor velocity v was estimated from the position measurement q by means of the high-pass filter represented in (9), which has a cut-off frequency of α = 20 1 rad/s. This filter was selected as the velocity estimation method in the simulation settings, whereas its parameter α 1 is set in the mCIT app as shown at the bottom of Figure 5.…”

“…The mCIT app executes the identification and control algorithms on the mobile device and allows users to interact with the experimental platform. Its GUI is based on the Control and Identification Toolbox (CIT) application described in Concha et al [9]. The main motivation behind the mCIT app design is to take advantage of the fact that most university students have mobile devices, and they have a positive attitude toward mobile learning [8,12].…”

Python app for drawing Bode diagram asymptotes of transfer function for minimum and non‐minimal phase systems

“…Python is even less used than MATLAB by scientists, but Python users are increasing every day; in Reference 15 it was shown how the use of open source tools like Jupiter notebook improves teachers and students productivity in engineering courses, providing flexibility and support for collaborative work and examples were presented for an Informatics Engineering courses; in Reference 16 it was shown that Jupyter/IPython notebooks is one of open source collaborative tools that provides an environment to develop and promote the access to remote and virtual labs and it was presented a IPython‐based approach to interact with a remote rain gauge to obtain data about the rainfall in a given location; in Reference 17 it was remarked that practical experiments are extremely important to engineering education and sciences and it was proposed a fully open source remote laboratory that can be used in all engineering education and applied sciences. That work was programmed in Python for a SCADA platform, Android app in Reference 18 it was presented a Control and Identification Toolbox (CTI) that performed in an Android platform with the purpose of teaching and learning the system response, automatic control and parameter identification of dynamic systems and Smartphone apps 19 …”

Universal fixed‐point digital controller for control theory studies

“…González‐Vargas et al proposed a low‐cost servomechanism control platform for educational purposes, based on a Real‐Time Application Interface for Linux (RTAI) [8]. Concha et al [4] presented an Android toolbox for teaching automatic control, including the calculation of system responses, and the parameter identification of dynamic systems. Although MATLAB/Simulink are used in many laboratories, field programmable gate arrays (FPGAs) are also used.…”