A Remote Laboratory as an Innovative Educational Tool for Practicing Control Engineering Concepts

This paper presents the development, structure, implementation, and some applications of a remote laboratory for teaching automatic control concepts to engineering students. There are two applications: formation control of mobile robots and a ball-plate system. In teaching control engineering, there are two main approaches to control design: model-based control and non-model-based control. Students are given insight into: 1) for model-based control: identification of real processes (i.e., dealing with noise, choosing the sampling time, observing nonlinear effects at startup, pairing input-output variables); and 2) for non-model-based control: the advantages and disadvantages of auto-tuning techniques. The paper concludes by presenting an evaluation of these remote labs and discussing the advantages of using them as complementary tools for teaching control engineering at the Bachelor's and Master's level.

[1]  D Kostic,et al.  Collision-free motion coordination of unicycle multi-agent systems , 2010, Proceedings of the 2010 American Control Conference.

[2]  J. Sweller,et al.  Cognitive Load Theory and Complex Learning: Recent Developments and Future Directions , 2005 .

[3]  Mauricio Ferreira Magalhães,et al.  Real: A Virtual Laboratory for Mobile Robot Experiments , 2001 .

[4]  S. Dormido,et al.  Adding interactivity to existing Simulink models using Easy Java Simulations , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[5]  Rihard Karba,et al.  Remote Multivariable Control Design Using a Competition Game , 2011, IEEE Transactions on Education.

[6]  Juan J. Fuertes-Martínez,et al.  Case-Based Reasoning and System Identification for Control Engineering Learning , 2008, IEEE Transactions on Education.

[7]  Yang Li,et al.  Identification of ball and plate system using multiple neural network models , 2012, 2012 International Conference on System Science and Engineering (ICSSE).

[8]  M. O. Hagler Preface to Special Issue on the Application of Information Technologies to Engineering and Science E , 1996 .

[9]  Robain De Keyser,et al.  The Next Generation of Relay-Based PID Autotuners (PART 1): Some Insights on the Performance of Simple Relay-Based PID Autotuners , 2012 .

[10]  Kevin C. Craig,et al.  Mechatronic design of a ball-on-plate balancing system , 2002 .

[11]  Robain De Keyser,et al.  A Remote Laboratory for Mobile Robot Applications , 2011 .

[12]  Lawrence A. Crowl,et al.  Distance learning applied to control engineering laboratories , 1996 .

[13]  R. De Keyser,et al.  Leader-follower string formation using cascade control for mobile robots , 2012, 2012 20th Mediterranean Conference on Control & Automation (MED).

[14]  P. Jayanetti,et al.  The making of multimedia power systems control and simulation labware , 1996 .

[15]  Pieter J. Mosterman,et al.  Design and implementation of an electronics laboratory simulator , 1996 .

[16]  Tore Hägglund,et al.  Automatic tuning of simple regulators with specifications on phase and amplitude margins , 1984, Autom..

[17]  Takanori Hirose,et al.  Preface to special issue , 2014, Brain Tumor Pathology.

[18]  Fernando Morilla,et al.  A Java/Matlab-based environment for remote control system laboratories: illustrated with an inverted pendulum , 2004, IEEE Transactions on Education.

[19]  Fumin Zhang,et al.  Robust Cooperative Exploration With a Switching Strategy , 2012, IEEE Transactions on Robotics.

[20]  Guanrong Chen,et al.  Formation control of networked multi-agent systems , 2010 .

[21]  Robin De Keyser,et al.  FRtool: A frequency response tool for CACSD in Matlab® , 2006, 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control.

[22]  Gonzalo Farias,et al.  Development of a Web-Based Control Laboratory for Automation Technicians: The Three-Tank System , 2008, IEEE Transactions on Education.

[23]  Francisco Esquembre,et al.  Easy Java Simulations: a software tool to create scientific simulations in Java , 2004 .

[24]  Anthony Mandow,et al.  Using LEGO NXT Mobile Robots With LabVIEW for Undergraduate Courses on Mechatronics , 2011, IEEE Transactions on Education.

[25]  Ii B. Oakley A virtual classroom approach to teaching circuit analysis , 1996 .

[26]  Sebastián Dormido-Bencomo,et al.  Control learning: present and future , 2004, Annu. Rev. Control..

[27]  Nader Engheta Preface To Special Issue , 1992 .

[28]  Fernando Torres Medina,et al.  EJS+EjsRL: An interactive tool for industrial robots simulation, Computer Vision and remote operation , 2011, Robotics Auton. Syst..

[29]  D V Dimarogonas,et al.  Multi-agent coordination with event-based communication , 2010, Proceedings of the 2010 American Control Conference.

[30]  W. Swart,et al.  A computer-aided, total quality approach to manufacturing education in engineering , 1996 .

[31]  Robin De Keyser,et al.  Developing Networked Control Labs: A Matlab and Easy Java Simulations Approach , 2010, IEEE Transactions on Industrial Electronics.

[32]  Robain De Keyser,et al.  The Next Generation of Relay-Based PID Autotuners (PART 2): A Simple Relay-Based PID Autotuner with Specified Modulus Margin , 2012 .

[33]  Alan J. Laub,et al.  Control System Toolbox User''s Guide , 1990 .