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A Reconfigurable and Modular Hardware for Remote Learning of Analog Circuit Design

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Middle Atlantic ASEE Section Spring 2021 Conference



Publication Date

April 9, 2021

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April 9, 2021

End Date

April 10, 2021

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Yixin Xiong Penn State University

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Yixin Xiong is a senior student at the Pennsylvania State University, majoring in Electrical Engineering with a concentration in circuits and electronics. His interests in circuits were developed in a music processing circuit design project in a major course, and enhanced in later higher-level circuits design courses. He is planning to attend graduate school after graduation to study deeper in this field.

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Stephen Porter Penn State University

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Stephen is a recent graduate of Penn State interested in discrete circuit design. He currently works in the high-tech product design industry.

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Swaroop Ghosh Pennsylvania State University

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Swaroop Ghosh received the B.E. (Hons.) from IIT, Roorkee, India, the M.S. degree from the University of Cincinnati, Cincinnati, and the Ph.D. degree from Purdue University, West Lafayette. He is an assistant Professor at Penn State University. Earlier, he was with the faculty of University of South Florida. Prior to that, he was a Senior Research and Development Engineer in Advanced Design, Intel Corp. At Intel, his research was focused on low power and robust embedded memory design in scaled technologies. His research interests include low-power circuits, hardware security, quantum computing and digital testing for nanometer technologies.

Dr. Ghosh served as Associate Editor of the IEEE Transactions On Computer-Aided Design (2019-) and IEEE Transactions On Circuits and Systems I (2014-2015) and as Senior Editorial Board member of IEEE Journal of Emerging Topics on Circuits and Systems (JETCAS) (2016-2018). He served as Guest Editor of the IEEE JETCAS (2015-2016) and IEEE Transactions On VLSI Systems (2018-2019). He has also served in the technical program committees of ACM/IEEE conferences such as, DAC, ICCAD, CICC, DATE, ISLPED, GLSVLSI, Nanoarch and ISQED. He served as Program Chair of ISQED (2019) and DAC Ph.D. Forum (2016) and track (co)-Chair of CICC (2017-2019), ISLPED (2017-2018) and ISQED (2016-2017).

Dr. Ghosh is a recipient of Intel Technology and Manufacturing Group Excellence Award in 2009, Intel Divisional Award in 2011, Intel Departmental Awards in 2011 and 2012, USF Outstanding Research Achievement Award in 2015, College of Engineering Outstanding Research Achievement Award in 2015, DARPA Young Faculty Award (YFA) in 2015, ACM SIGDA Outstanding New Faculty Award in 2016, YFA Director’s Fellowship in 2017, Monkowsky Career Development Award in 2018, Lutron Spira Teaching Excellence Award in 2018 and Dean's Certificate of Excellence in 2019. He is a Senior member of the IEEE and the National Academy of Inventors (NAI), and, Associate member of Sigma Xi. He serves as a Distinguished Speaker of the Association for Computing Machinery (ACM) for a 3 year term (2019-2022).

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COVID-19 has precluded a large number of undergraduate students from entering the lab and gaining hands-on experience for theoretical concepts taught in online classes. This has affected the conceptual understanding of the topics and degraded student motivation. We developed a Do-It-Yourself (DIY) compose-able virtual hardware board (located in a lab remotely) to enable remote learning for courses such as analog circuit design. The board consists of remotely selectable hardware components such as transistors, logic gates (combinational and sequential), and passive (e.g., resistors and capacitors) components using multiplexers controlled through myDAQ (a commercially available hardware that interfaces with the board). These components can be composed on a breadboard to create the desired circuit (such as common source amplifier with specified gain) remotely by sending commands to the myDAQ by a software interface for virtual experiments. The output of the board can be digitized and sent to the student's PC for visualization. The proposed setup can be time-shared with multiple students and can also be easily replicated. This framework is modular (i.e., other components like an extra breadboard with new designs can be added) and is also useful in the longer-term by allowing the students to personalize their learning.

Board design: The design of the whole system consists of two parts--board and controller. In the board design, we created simple common-source and differential amplifier circuits. In order to help students learn the effect of load and biasing points, two different loads were set up using different loading resistors. Various bias voltages are accomplished by using voltage dividers so that the MOSFETs can work in two different areas of operation. Each of the bias and load settings is user selectable. To switch between various circuit configurations, analog switches are utilized. In addition, the multiplexers are used to decode the digital control signal from the controller to actual signals that control the analog switches. The values of the resistors in the load are set to provide a proper gain and the resistor in the voltage dividers are fine-tuned using potentiometers. The complete circuits are created first and the analog switches are added later. Due to the relatively low on-resistance, the added analog switches have minimal effect on the pre-designed circuit. In the controller design, LabVIEW has been chosen as a programming language and myDAQ has been chosen as a cheap alternative to costly instruments. A user interface has been designed by using this hardware and software to control the circuit and read the resulting output signal through a computer. The functionality of the board has been validated experimentally.

Conclusions: We developed a modular, remote reconfigurable, and reproducible hardware board to help students conduct their experiments remotely. The board has been validated for multiple amplifier circuits.

Xiong, Y., & Porter, S., & Ghosh, S. (2021, April), A Reconfigurable and Modular Hardware for Remote Learning of Analog Circuit Design Paper presented at Middle Atlantic ASEE Section Spring 2021 Conference, Virtual . 10.18260/1-2--36281

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