Enhancing Technical Skills of Control Engineering

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This section discusses the introduction of the LabVIEW- based teaching/ learning tools ... to the control and computer science engineering students. The learning ...
Enhancing Technical Skills of Control Engineering Students In Robotics by using Common Software Tools and Developping Experimental Platforms Amira Aloulou and Olfa Boubaker Department of Physics and Instrumentation National Institute of Applied Sciences and Technology, INSAT Centre Urbain Nord BP. 676 – 1080 Tunis Cedex, Tunisia

Abstract—In this paper, we expose a successful approach of a course project aiming to improve technical skills of engineering students by encouraging them to use common software tools and developing experimental platforms. The course is dedicated to advanced undergraduate control engineering students. Only two experimental platforms, among twenty projects, developed by the students as part of the course are exposed. The two projects use LabVIEW programming environment, its data acquisition platform and a wide-ranging set of tools for analyzing, displaying and storing data. The main objective of such education approach is to produce qualified engineers who are ready for innovation in research and industry careers, able to share results and collaborate with international projects. Recruitment results have shown that employers have more confidence in the technical abilities of our students for creating new business opportunities which could enhance their recruitment criteria.

integrates many thousands of hardware devices which can be used with a single development environment. Many prestigious universities and colleges are currently incorporating National Instruments® LabVIEW™ software as teaching, measurement and analysis tool for student learning. Table 1 gives a bibliographical review of the main applications using LabVIEW programming environment in the field of control engineering education. TABLE I.

Disciplines Control engineering

Keywords; Control Engineering, education, Robotics, Computer Vision Software, experimental platforms, recruitment criteria.

I.

INTRODUCTION

National Instruments® LabVIEW™ is considered, nowadays, as the most professional software, among others, for data acquisition, data analysis, real time and remote control [1]. The LabVIEW environment [2] contains a wide-ranging set of tools for acquiring, analyzing, displaying, and storing data. LabVIEW software is also used to communicate with many hardware devices such as vision and motion control devices, GPIB, PXI and RS-232 devices. The main characteristic that distinguishes LabVIEW from other data acquisition programs is its highly modular graphical programming language, "G," and a great library of functions [3], toolkits and modules. LabVIEW environment is famous for its flexibility, reusability, self-documentation modularity, multi-platform portability, and compatibility with existing code and with different interface hardware [4]. LabVIEW software is distinguished by its extendible libraries and its multi-advanced debugging features. It is also characterized by an intuitive Graphical User Interface (GUI) and Multimedia capabilities for future developments. Furthermore, it is possible to create stand-alone executables and share libraries. LabVIEW

MULTI-DISCIPLINARY APPLICATIONS OF LABVIEW ENVIRONMENT References [5], [6]

Robotics

[7], [8], [9]

Mechatronic engineering

[10], [11]

Aerospace and Mechanical engineering

[12]

Electro-Mechanical engineering

[13]

Electronic engineering

[14], [15]

Electrical machines

[16] [17]

Power electronics

[18] [19] [20]

This paper exposes a successful approach of a course project aiming to improve technical skills of control engineering students by encouraging them to use National Instruments® LabVIEW™ software to develop experimental robotics platforms. II.

LABVIEW WITHIN THE NEW CURRICULUM OF INSAT

This section discusses the introduction of the LabVIEWbased teaching/ learning tools within the new curriculum [21] of National Institute of Applied Sciences and Technology (INSAT) at Tunisia launched in 2010 year. These activities will be introduced in the second semester of the second year offered to the control and computer science engineering students. The learning methodology, in this year, consisted of four stages: − An introductory learning period for the LabVIEW™ programming language and Hardware environment [22, 23].



An Application learning period aiming at solving a set of specific software exercises using LabVIEW environment [24, 25]. − A designing and developing LabVIEW project period aiming to acquire knowledge by direct experiences on experimental platforms developed by engineering students. − One-hour multiple-choice test: the Certified LabVIEW Associate Developer (CLAD) exam to prove the student technical competency. NI CLAD Certification and experimental platforms developed by engineering student’s aims to prove that students have sufficient skills to create high-quality applications with standard platforms. It gives employers confidence in the technical abilities of our students to create new business opportunities. III.

circuits, respectively. The vision acquisition code and the control user interface are shown by Fig.4 and Fig.5 respectively.

Figure 2. Proteus CAD for DC Motor control

EXPERIMENTAL PLATFORMS DEVELOPED BY STUDENTS AS PART OF THE COURSE

This section exposes two examples between twenty experimental platforms developed by the second year control and computer science students engineering of INSAT as part of a new course of the new curriculum. A. Project 1: A Computer Vision System for Robot Control The purpose of this project is to design and implement a realtime vision system for interpreting human gestures [26, 27, 28] via LabVIEW software and its Vision tools. As seen in Fig.1, the Vision platform developed by students for interpreting human gestures is composed by a Webcam, a DC motor, a dark support on which the hand is placed and a LabVIEW User Interface for acquiring and analyzing data.

Figure 3. Proteus CAD for RS232 communication

Figure 4. LabVIEW Code for vision acquisition

Figure 1. Vision platform for interpreting human gestures

Fig. 2 and Fig.3 show the CAD design via Proteus software of the motor controller and the RS-232 port communication

The DC motor can be either controlled by a numerical input (presence or absence of the hand) as can be seen by Fig. 5 or by an analog input as can be seen by Fig.6, Fig.7 and Fig.8 which are respectively representing three scenarios for controlling de DC motor. An experimental validation of the vision platform for interpreting human gestures is found in [29].

In future investigation, such platform can be applied to control the pattern walking generator of the humanoid robot described in [30, 31, 32]. B. Project 2: Design and Control of a robotic arm

Figure 5. LabVIEW Control User Interface

The second project aims to design a 4 DOF robot and control the robotic arm via an USB communication and a LabVIEW User Interface. The robotic prototype is shown by Fig.9 whereas the design of test verification circuit via Proteus VSM software is shown by Fig.10. Experimental platform, developed by students, is shown by Fig.11. The LabVIEW User Interface and the LabVIEW Code for USB acquisition system and robot control are shown by Fig.12 and Fig.13, respectively. In future works, our first objective is to study the structural identifiability for model parameter identification [33]. An experimental validation of the robotic arm can be found in [34]. In future investigation, the developed system can be used as an experimental platform to test the gain scheduling control approach proposed in [35] for the unconstrained robot or the position/force control approaches exposed in [36, 37, 38, 39] for the constrained robot.

Figure 6. Test Validation : Scenario 1

Figure 7. Test Validation : Scenario 2

Figure 9. Computer Aided Design of the robotic arm via Solidworks software

Figure 10. Design of test verification circuit via Proteus VSM software Figure 8. Test Validation : Scenario 3

ready for innovation in research and industry careers and enhance recruitment criteria. REFERENCES [1]

[2] [3]

[4] Figure 11. Experimental robotic platform

[5] [6]

[7]

[8]

[9] Figure 12. LabVIEW Human-Machine User Interface

[10]

[11]

[12]

[13]

[14]

[15]

[16] Figure 13. LabVIEW Code for USB acquisition system [17]

IV.

CONCLUSION

In this paper we have exposed a course project encouraging control engineering students to enhance their technical skills by using common professional tools and developing experimental platform. Using such approach in engineering education certainly help educators to produce qualified engineers who are

[18]

O. Boubaker, “National Instruments LabVIEW: Ultimate Software for Engineering Education,” Int. Conf. on Frontiers in Education: Computer Science and Computer Engineering, Las Vegas, Nevada, USA, pp.18-21 July 2011. The National Instruments® LabVIEW™ Corporation website. http://www.ni.com/labview/. C. J. Kalkman, “LabVIEW: A software system for data acquisition, data analysis, and instrument control,” J. of Clinical Monitoring, vol. 11, n°1, pp. 51-58, 1995. B. Balamuralithara and P. C. Woods, “Virtual laboratories in engineering education: The simulation lab and remote lab,” Computer Applications in Engineering Education, vol. 17, n°1, pp.108-118, 2009. J.P. Keller, “Teaching PID and fuzzy controllers with LabVIEW,” Int. J. of Engineering Education, vol. 16, n°3, pp. 202-211, 2000. S. Daniels, D. Harding and M. Collura, “Introducing feedback control to first year engineering students using LabVIEW,” Proc. of the Annual Conf. and Exposition: The Changing Landscape of Engineering and Technology Education in a Global World, 2005. B. Erwin, M. Cyr and C. Rogers, “LEGO engineer and RoboLab: Teaching engineering with LabVIEW from kindergarten to graduate school,” Int. J. of Engineering Education, vol. 16, n°3, pp. 181-192, 2000. J.M., Gomez-de-Gabriel, A. Mandow, J. Fernandez-Lozano and A. Garcia-Cerezo, “Using LEGO NXT mobile robots with LabVIEW for undergraduate courses on mechatronics,” IEEE Trans. on Education, vol. 54, n°1, pp. 41 - 47, 2011. V. Wilczynski, J. S. Mittelman and N. Lim, “2,000 robotic applications using the national instruments CompactRIO embedded control system,” Proc. of the IEEE Int. Conf. on Technologies for Practical Robot Applications, 2009. M. Ghone and J. Wagner, “A multi-disciplinary mechatronics laboratory,” Proc. of the of American Society for Engineering Education Conference, 2003. W. Benrejeb and O. Boubaker, “FPGA Modeling and Real-Time Embedded Control Design via LabVIEW Software: Application for Swinging-Up a Pendulum,” Int. J. on Smart Sensing and Intelligent Systems, Vol. 5, N°2, 2012. F.K. Lu, P.K. Panicker and M.B. Webb, “Introducing modern laboratory experiences to mechanical and aerospace engineering students,” Proc. of the Int. Mechanical Engineering Congress and Exposition, 2008. R. Alba-Flores and D. Hunt, “Incorporating LabVIEW to enhance the learning experience in the electromechanical analysis laboratory,” Proc. of the ASEE Annual Conf. and Exposition, 2008. R. Kilic and B. Karauz, “Chaos training boards: Versatile pedagogical tools for teaching chaotic circuits and systems,” Int. J. of Engineering Education, vol. 24, n° 3, pp. 634-644, 2008. Y. Zhou, J. J. Jiang and S. C. Fan, “A LabVIEW-based, interactive virtual laboratory for electronic engineering education,” Int. J. of Engineering Education, vol. 21, n°1, pp. 94-102, 2005. D. G. Kasten, “Integrating computerized data acquisition and analysis into an undergraduate electric machines laboratory,” Proc. of the Frontiers in Education Conference 2000. F. S. Sellschopp and M. A. Arjona, “An automated system for frequency response analysis with application to an undergraduate laboratory of electrical machines,” IEEE Trans. on Education, vol. 47, n°1, pp. 57-64, 2004. J. M. Jiménez-Martínez, F. Soto, E. de Jódar, J. A. Villarejo and J. Roca-Dorda, “A new approach for teaching power electronics converter experiments,” IEEE Trans. on Education, vol. 48, n°3, pp. 513-519, 2005.

[19] P. Spanik, L. Hargas, M. Hrianka and I. Kozehuba, “Application of virtual instrumentation labVIEW for power electronic system analysis,” Proc. of the Int. Power Electronics and Motion Control Conference, 2007 . [20] N. Patrascoiu, “Modeling and simulation of the DC motor using MatLAB and LabVIEW,” Int. J. of Engineering Education, vol. 21, n°1, pp. 49-54, 2005. [21] INSAT website, New Engineer Teaching Program, http://www.insat.rnu. tn/images/pdf/programme-ingenieur_new-regime.pdf. [22] LabVIEWTM Core 1 Course Manual, National Instruments Corporation, 2009. [23] LabVIEWTM Core 2 Course Manual, National Instruments Corporation, 2009. [24] LabVIEWTM Core 1 Exercices, National Instruments Corporation, 2009. [25] LabVIEWTM Core 2 Exercices, National Instruments Corporation, 2009. [26] V. Pavlovic, R. Sharma, T. Huang, Visual interpretation of hand gestures for human-computer interaction: A review,” IEEE Trans. Pattern Analysis and Machine Intelligence., Vol. 19, n°7, pp. 677 -695, 1997. [27] Y. Wu and T.S. Huang, “Vision-Based Gesture Recognition: A Review,” Gesture-Based Communication in Human-Computer Interaction, vol. 1739, Springer Lecture Notes in Computer Science, pp. 103-115, 1999. [28] K. Nickel and R. Stiefelhagen, “Visual recognition of pointing gestures for human-robot interaction,” Image and Vision Computing, vol 25, N°12, 2007, pp 1875-1884. [29] Human gesture recognition control video: http://www.youtube.com/ watch?v=I6i4y7MjPOY

[30] A. Aloulou and O. Boubaker, “Control of a Step Walking Combined to Arms Swinging for a three Dimensional Humanoid Prototype,” J. of Computer Science, Vol. 6, N° 8, 2010, pp. 886-895. [31] A. Aloulou and O. Boubaker, “Minimum Jerk-based Control for a Three Dimensional Bipedal Robot,” Lecture Notes In Computer Science, Vol. 7102, pp. 251-262, 2011. [32] Y. Arous and O. Boubaker, “Gait Trajectory Generation for a Five Link Bipedal Robot Based on a Reduced Dynamical Model,” IEEE Mediterranean Electro-technical Conf., Yasmine Hammamet, Tunisia, 25-28 Mars 2012, pp. 993-996. [33] O. Boubaker and A. Fourati, “Structural identifiability of non linear systems: an overview,” IEEE Conf. on Industrial Technology, vol. 3, pp. 1244 - 1248, 2004. [34] Robotic arm control video: http://www.youtube.com/watch?v=MUQR xGud5s0 [35] O. Boubaker,“Gain scheduling control: an LMI approach,” Int. Review of Electrical Engineering, Vol. 3, April 2008, pp. 378-385. [36] H. Mehdi and O. Boubaker, “Stiffness and Impedance Control using Lyapunov Theory for Robot-aided Rehabilitation,” Int. J. of Social Robotics, Vol. 4, N°2, 2012. [37] H. Mehdi and O. Boubaker, “Impedance Controller Tuned by Particle Swarm Optimization for Robotic Arms,” Int. J. of Advanced Robotic Systems, Vol.8, N°5, pp.93-103, 2011. [38] H. Mehdi and O. Boubaker, “Rehabilitation of a Human Arm Supported by a Robotic Manipulator: A Position/Force Cooperative Control”, J. of Computer Science, Vol.6, N° 8, pp. 912-919, 2010. [39] H. Mehdi and O. Boubaker, “Position/Force Control Optimized by Particle Swarm Intelligence for Constrained Robotic Manipulators,” IEEE Int. Conf. on Intelligent Systems Design and Applications (ISDA’2011), Córdoba, Spain, pp. 190 – 195, 22-24 November, 2011.