0
Research Papers

An Iterative Learning Control Approach to Improving Fidelity in Internet-Distributed Hardware-in-the-Loop Simulation

[+] Author and Article Information
Tulga Ersal

Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: tersal@umich.edu

Mark Brudnak

The US Army Tank-Automotive Research,
Development and Engineering Center,
Warren, MI 48397
e-mail: mark.j.brudnak.civ@mail.mil

Ashwin Salvi

Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: asalvi@umich.edu

Youngki Kim

Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: youngki@umich.edu

Jason B. Siegel

Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: siegeljb@umich.edu

Jeffrey L. Stein

Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: stein@umich.edu

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received July 16, 2013; final manuscript received June 12, 2014; published online August 8, 2014. Assoc. Editor: Gregory Shaver. This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. Approved for public release; distribution is unlimited.

J. Dyn. Sys., Meas., Control 136(6), 061012 (Aug 08, 2014) (8 pages) Paper No: DS-13-1276; doi: 10.1115/1.4027868 History: Received July 16, 2013; Revised June 12, 2014

One of the main challenges of cosimulating hardware-in-the-loop (HIL) systems in real-time over the Internet is the fidelity of the simulation. The dynamics of the Internet may significantly distort the dynamics of the network-integrated system. This paper presents the development and experimental validation of an iterative learning control (ILC) based approach to improve fidelity of such networked system integration. Toward this end, a new metric for characterizing coupling fidelity is proposed, which, unlike some existing metrics, enables the formulation of the problem of improving system fidelity without requiring any knowledge about the reference dynamics (i.e., dynamics that would be observed, if the system was physically connected). Next, using this metric, the problem of improving fidelity is formulated as an ILC problem. The proposed approach is illustrated on an experimental setup simulating a hybrid electric powertrain distributed across three different sites with a real engine and battery in the loop. The conclusion is that the proposed approach holds significant potential for achieving high fidelity in Internet-distributed HIL (ID-HIL) simulation setups.

FIGURES IN THIS ARTICLE
<>
Copyright © 2014 by ASME
Your Session has timed out. Please sign back in to continue.

References

Fathy, H. K., Filipi, Z. S., Hagena, J., and Stein, J. L., 2006, “Review of Hardware-in-the-Loop Simulation and Its Prospects in the Automotive Area,” SPIE—Modeling and Simulation for Military Applications , Kissimmee, FL, Apr. 18–21, Vol. 6228, pp. 1–20.
Kimura, A., and Maeda, I., 1996, “Development of Engine Control System Using Real Time Simulator,” IEEE International Symposium on Computer-Aided Control System Design, Dearborn, MI, Sep. 15–18, pp. 157–163.
Verma, R., Del Vecchio, D., and Fathy, H. K., 2008, “Development of a Scaled Vehicle With Longitudinal Dynamics of an HMMWV for an ITS Testbed,” IEEE/ASME Trans. Mechatron., 13(1), pp. 46–57. [CrossRef]
Leitner, J., 2001, “A Hardware-in-the-Loop Testbed for Spacecraft Formation Flying Applications,” IEEE Aerospace Conference, Big Sky, MT, Mar. 10–17, Vol. 2, pp. 615–620.
Yue, X., Vilathgamuwa, D. M., and Tseng, K.-J., 2005, “Robust Adaptive Control of a Three-Axis Motion Simulator With State Observers,” IEEE/ASME Trans. Mechatron., 10(4), pp. 437–448. [CrossRef]
Ganguli, A., Deraemaeker, A., Horodinca, M., and Preumont, A., 2005, “Active Damping of Chatter in Machine Tools—Demonstration With a ‘Hardware-in-the-Loop’ Simulator,” J. Syst. Control Eng., 219(5), pp. 359–369. [CrossRef]
Aghili, F., and Piedboeuf, J.-C., 2002, “Contact Dynamics Emulation for Hardware-in-Loop Simulation of Robots Interacting With Environment,” IEEE International Conference on Robotics and Automation, Washington, DC, May 11–15, Vol. 1, pp. 523–529.
White, G. D., Bhatt, R. M., Tang, C. P., and Krovi, V. N., 2009, “Experimental Evaluation of Dynamic Redundancy Resolution in a Nonholonomic Wheeled Mobile Manipulator,” IEEE/ASME Trans. Mechatron., 14(3), pp. 349–357. [CrossRef]
Buford, J. A., Jr., Jolly, A. C., Mobley, S. B., and Sholes, W. J., 2000, “Advancements in Hardware-in-the-Loop Simulations at the U.S. Army Aviation and Missile Command,” SPIE—Technologies for Synthetic Environments: Hardware-in-the-Loop Testing V, R. L. Murrer, ed., Orlando, FL, Apr. 24–26, Vol. 4027, pp. 2–10.
Huber, E. G., Jr., and Courtney, R. A., 1997, “Hardware-in-the-Loop Simulation at Wright Laboratory's Dynamic Infrared Missile Evaluator (Dime) Facility,” Technologies for Synthetic Environments: Hardware-in-the-Loop Testing II, Orlando, FL, Apr. 21–23, Vol. 3084, pp. 2–8.
Mahin, S., Nigbor, R., Pancake, C., Reitherman, R., and Wood, S., 2003, “The Establishment of the NEES Consortium,” ASCE/SEI Structures Congress and Exposition: Engineering Smarter, Seattle, WA, May 29–31, pp. 181–182.
Spencer, B. F., Elnashai, A., Nakata, N., Saliem, H., Yang, G., Futrelle, J., Glick, W., Marcusiu, D., Ricker, K., Finholt, T., Horn, D., Hubbard, P., Keahey, K., Liming, L., Zaluzec, N., Pearlman, L., and Stauffer, E., 2004, “The Most Experiment: Earthquake Engineering on the Grid,” Technical Report NEESgrid-2004-41, NEESgrid.
Pan, P., Tada, M., and Nakashima, M., 2005, “Online Hybrid Test by Internet Linkage of Distributed Test-Analysis Domains,” Earthquake Eng. Struct. Dyn., 34(11), pp. 1407–1425. [CrossRef]
Stojadinovic, B., Mosqueda, G., and Mahin, S. A., 2006, “Event-Driven Control System for Geographically Distributed Hybrid Simulation,” J. Struct. Eng., 132(1), pp. 68–77. [CrossRef]
Takahashi, Y., and Fenves, G. L., 2006, “Software Framework for Distributed Experimental-Computational Simulation of Structural Systems,” Earthquake Eng. Struct. Dyn., 35(3), pp. 267–291. [CrossRef]
Mosqueda, G., Stojadinovic, B., Hanley, J., Sivaselvan, M., and Reinhorn, A. M., 2008, “Hybrid Seismic Response Simulation on a Geographically Distributed Bridge Model,” J. Struct. Eng., 134(4), pp. 535–543. [CrossRef]
Compere, M., Goodell, J., Simon, M., Smith, W., and Brudnak, M., 2006, “Robust Control Techniques Enabling Duty Cycle Experiments Utilizing a 6-DOF Crewstation Motion Base, a Full Scale Combat Hybrid Electric Power System, and Long Distance Internet Communications,” SAE Technical Paper No. 2006-01-3077. [CrossRef]
Goodell, J., Compere, M., Simon, M., Smith, W., Wright, R., and Brudnak, M., 2006, “Robust Control Techniques for State Tracking in the Presence of Variable Time Delays,” SAE Technical Paper No. 2006-01-1163. [CrossRef]
Brudnak, M., Pozolo, M., Paul, V., Mohammad, S., Smith, W., Compere, M., Goodell, J., Holtz, D., Mortsfield, T., and Shvartsman, A., 2007, “Soldier/Harware-in-the-Loop Simulation-Based Combat Vehicle Duty Cycle Measurement: Duty Cycle Experiment 2,” Simulation Interoperability Workshop, Norfolk, VA, Mar. 25–30, SIW-07S-016.
Ersal, T., Brudnak, M., Salvi, A., Stein, J. L., Filipi, Z., and Fathy, H. K., 2011, “Development and Model-Based Transparency Analysis of an Internet-Distributed Hardware-in-the-Loop Simulation Platform,” Mechatronics, 21(1), pp. 22–29. [CrossRef]
Ersal, T., Brudnak, M., Stein, J. L., and Fathy, H. K., 2012, “Statistical Transparency Analysis in Internet-Distributed Hardware-in-the-Loop Simulation,” IEEE/ASME Trans. Mechatron., 17(2), pp. 228–238. [CrossRef]
Ersal, T., Gillespie, R. B., Brudnak, M., Stein, J. L., and Fathy, H. K., 2013, “Effect of Coupling Point Selection on Distortion in Internet-Distributed Hardware-in-the-Loop Simulation,” Int. J. Veh. Des., 61(1–4), pp. 67–85. [CrossRef]
Tandon, A., Brudnak, M. J., Stein, J. L., and Ersal, T., 2013, “An Observer Based Framework to Improve Fidelity in Internet-Distributed Hardware-in-the-Loop Simulations,” ASME Paper No. DSCC2013-3878. [CrossRef]
Kim, Y., Salvi, A., Stefanopoulou, A., and Ersal, T., “Reducing Soot Emissions in a Diesel Series Hybrid Electric Vehicle Using a Power Rate Constraint Map,” IEEE Trans. Veh. Tech. (in press) [CrossRef]
Kress, R. L., Hamel, W. R., Murray, P., and Bills, K., 2001, “Control Strategies for Teleoperated Internet Assembly,” IEEE/ASME Trans. Mechatron., 6(4), pp. 410–416. [CrossRef]
Elhajj, I., Tan, J., Xi, N., Fung, W. K., Liu, Y. H., Kaga, T., Hasegawa, Y., and Fukuda, T., 2002, “Multi-Site Internet-Based Tele-Cooperation,” Integr. Comput.-Aided Eng., 9(2), pp. 117–127.
Munir, S., and Book, W. J., 2002, “Internet-Based Teleoperation Using Wave Variables With Prediction,” IEEE/ASME Trans. Mechatron., 7(2), pp. 124–133. [CrossRef]
Niemeyer, G., and Slotine, J.-J. E., 2002, “Toward Bilateral Internet Teleoperation,” Beyond Webcams: An Introduction to Online Robots, MIT Press, Cambridge, MA, pp. 193–213.
Sun, L.-N., Xie, X.-H., Fu, L.-X., and Du, Z.-J., 2003, “Internet-Based Telerobotic Surgery: Problems and Approaches,” Harbin Gongye Daxue Xuebao/J. Harbin Inst. Technol., 35(2), pp. 129–133.
Shi, Y.-H., and Wang, Y.-C., 2004, “Study on Internet-Based Force Feedback Technology,” Robot, 26(4), pp. 330–335.
Slawinski, E., Postigo, J. F., and Mut, V., 2007, “Bilateral Teleoperation Through the Internet,” Rob. Auton. Syst., 55(3), pp. 205–215. [CrossRef]
Chopra, N., Berestesky, P., and Spong, M. W., 2008, “Bilateral Teleoperation Over Unreliable Communication Networks,” IEEE Trans. Control Syst. Technol., 16(2), pp. 304–313. [CrossRef]
Lawrence, D. A., 1993, “Stability and Transparency in Bilateral Teleoperation,” IEEE Trans. Rob. Autom., 9(5), pp. 624–637. [CrossRef]
Hashtrudi-Zaad, K., and Salcudean, S. E., 2002, “Transparency in Time-Delayed Systems and the Effect of Local Force Feedback for Transparent Teleoperation,” IEEE Trans. Rob. Autom., 18(1), pp. 108–114. [CrossRef]
Fite, K. B., Speich, J. E., and Goldfarb, M., 2001, “Transparency and Stability Robustness in Two-Channel Bilateral Telemanipulation,” ASME J. Dyn. Syst., Meas. Control, 123(3), pp. 400–407. [CrossRef]
Çavuşoğlu, M. C., Sherman, A., and Tendick, F., 2002, “Design of Bilateral Teleoperation Controllers for Haptic Exploration and Telemanipulation of Soft Environments,” IEEE Trans. Robo. Autom., 18(4), pp. 641–647. [CrossRef]
De Gersem, G., Van Brussel, H., and Tendick, F., 2005, “Reliable and Enhanced Stiffness Perception in Soft-Tissue Telemanipulation,” Int. J. Rob. Res., 24(10), pp. 805–822. [CrossRef]
Yokokohji, Y., and Yoshikawa, T., 1994, “Bilateral Control of Master-Slave Manipulators for Ideal Kinesthetic Coupling—Formulation and Experiment,” IEEE Trans. Rob. Autom., 10(5), pp. 605–619. [CrossRef] [PubMed]
Yokokohji, Y., Imaida, T., and Yoshikawa, T., 1999, “Bilateral Teleoperation Under Time-Varying Communication Delay,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'99): Human and Environment Friendly Robots With High Intelligence and Emotional Quotients', Kyongju, South Korea, Oct. 17–21, Vol. 3, pp. 1854–1859.
Griffiths, P. G., Gillespie, R. B., and Freudenberg, J. S., 2011, “A Fundamental Linear Systems Conflict Between Performance and Passivity in Haptic Rendering,” IEEE Trans. Rob., 27(1), pp. 75–88. [CrossRef]
Griffiths, P. G., Gillespie, R. B., and Freudenberg, J. S., 2008, “A Fundamental Tradeoff Between Performance and Sensitivity Within Haptic Rendering,” IEEE Trans. Rob., 24(3), pp. 537–548. [CrossRef]
Freudenberg, J. S., Hollot, C. V., Middleton, R. H., and Toochinda, V., 2003, “Fundamental Design Limitations of the General Control Configuration,” IEEE Trans. Autom. Control, 48(8), pp. 1355–1370. [CrossRef]
Bristow, D. A., Tharayil, M., and Alleyne, A. G., 2006, “A Survey of Iterative Learning Control: A Learning-Based Method for High-Performance Tracking Control,” IEEE Control Syst. Mag., 26(3), pp. 96–114. [CrossRef]
Xu, J.-X., and Tan, Y., 2002, “Robust Optimal Design and Convergence Properties Analysis of Iterative Learning Control Approaches,” Automatica, 38(11), pp. 1867–1880. [CrossRef]
Wang, D., 2000, “On D-Type and P-Type ILC Designs and Anticipatory Approach,” Int. J. Control, 73(10), pp. 890–901. [CrossRef]
Cheah, C.-C., and Wang, D., 1998, “Learning Impedance Control for Robotic Manipulators,” IEEE Trans. Rob. Autom., 14(3), pp. 452–465. [CrossRef]
Chien, C.-J., and Liu, J.-S., 1996, “A P-Type Iterative Learning Controller for Robust Output Tracking of Nonlinear Time-Varying Systems,” Int. J. Control, 64(2), pp. 319–334. [CrossRef]
Heinzinger, G., Fenwick, D., Paden, B., and Miyazaki, F., 1992, “Stability of Learning Control With Disturbances and Uncertain Initial Conditions,” IEEE Trans. Autom. Control, 37(1), pp. 110–114. [CrossRef]
Park, K.-H., Bien, Z., and Hwang, D.-H., 1999, “A Study on the Robustness of a PID-Type Iterative Learning Controller Against Initial State Error,” Int. J. Syst. Sci., 30(1), pp. 49–59. [CrossRef]
Saab, S. S., 2003, “Stochastic P-Type/D-Type Iterative Learning Control Algorithms,” Int. J. Control, 76(2), pp. 139–148. [CrossRef]
Horowitz, R., 1993, “Learning Control of Robot Manipulators,” ASME J. Dyn. Syst., Meas. Control, 115(2B), pp. 402–411. [CrossRef]
Havlicsek, H., and Alleyne, A., 1999, “Nonlinear Control of an Electrohydraulic Injection Molding Machine Via Iterative Adaptive Learning,” IEEE/ASME Trans. Mechatron., 4(3), pp. 312–323. [CrossRef]
Arimoto, S., Kawamura, S., and Miyazaki, F., 1984, “Bettering Operation of Robots by Learning,” J. Rob. Syst., 1(2), pp. 123–140. [CrossRef]
Ersal, T., Brudnak, M., and Stein, J. L., 2012, “An Iterative Learning Control Approach to Improving Fidelity in Internet-Distributed Hardware-in-the-Loop Simulation,” ASME Paper No. DSCC2012-MOVIC2012-8677. [CrossRef]
Filipi, Z. S., Fathy, H. K., Hagena, J., Knafl, A., Ahlawat, R., Liu, J., Jung, D., Assanis, D. N., Peng, H., and Stein, J. L., 2006, “Engine-in-the-Loop Testing for Evaluating Hybrid Propulsion Concepts and Transient Emissions—HMMWV Case Study,” SAE World Congress, Detroit, MI, Paper No. 2006-01-0443.
Kim, Y., Ersal, T., Salvi, A., Filipi, Z., and Stefanopoulou, A., 2012, “Engine-in-the-Loop Validation of a Frequency Domain Power Distribution Strategy for Series Hybrid Powertrains,” IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling, Rueil-Malmaison, France, Oct. 23–25.
Mills, D. L., 1998, “Adaptive Hybrid Clock Discipline Algorithm for the Network Time Protocol,” IEEE-ACM Trans. Networking, 6(5), pp. 505–514. [CrossRef]
Lee, T.-K., Kim, Y., Stefanopoulou, A., and Filipi, Z. S., 2011, “Hybrid Electric Vehicle Supervisory Control Design Reflecting Estimated Lithium-Ion Battery Electrochemical Dynamics,” American Control Conference, ACC 2011, San Francisco, CA, June 29–July, pp. 388–395.
Argonne National Laboratory, 2002, “Powertrain Systems Analysis Toolkit,” Date Accessed: Nov. 19, 2013, http://www.transportation.anl.gov/software/PSAT
Kim, Y., Salvi, A., Siegel, J. B., Filipi, Z., Stefanopoulou, A., and Ersal, T., “Hardware-in-the-Loop Validation of a Power Management Strategy for Hybrid Powertrains,” Control Eng. Pract., 29, pp. 277–286. [CrossRef]

Figures

Grahic Jump Location
Fig. 1

Illustration of defining the errors in the coupling variables toward characterizing fidelity in ID-HIL on an example with two sites (Systems 1 and 2). ci,j represents the i-th coupling variable on the system j side of the network, and ei represents the instantaneous error in the i-th coupling variable.

Grahic Jump Location
Fig. 2

Proposed ILC-based framework for iteratively improving ID-HIL fidelity. This figure illustrates a decentralized approach in which an independent ILC controller is utilized for each coupling variable.

Grahic Jump Location
Fig. 3

The overview of the system considered in the case study. Each shaded region corresponds to a different geographic location. Italic typeface denotes physical components; the remaining components are modeled.

Grahic Jump Location
Fig. 4

A photo of the engine-in-the-loop testing facility

Grahic Jump Location
Fig. 5

The battery testing laboratory

Grahic Jump Location
Fig. 6

Packet delays observed during a network characterization test

Grahic Jump Location
Fig. 7

The speed profile used in the case study is a portion of the Urban Assault Cycle

Grahic Jump Location
Fig. 8

ILC performance in the case study

Grahic Jump Location
Fig. 9

Improvement in the fidelity of some output variables due to the proposed ILC framework

Grahic Jump Location
Fig. 10

Battery power as a representative system response to illustrate how internet delay can affect system dynamics and how the proposed method can alleviate its negative impact

Grahic Jump Location
Fig. 11

Efficiency contour map of an electric motor superimposed by maximum and continuous torque

Grahic Jump Location
Fig. 12

BSFC of engine/generator unit obtained by combining engine BSFC and generator efficiency and superimposed by optimal operation lines of the engine/generator unit and the engine only

Grahic Jump Location
Fig. 13

The schematic diagram of the FDPD strategy

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In