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.
An Iterative Learning Control Approach to Improving Fidelity in Internet-Distributed Hardware-in-the-Loop Simulation
e-mail: tersal@umich.edu
Development and Engineering Center,
e-mail: mark.j.brudnak.civ@mail.mil
e-mail: asalvi@umich.edu
e-mail: youngki@umich.edu
e-mail: siegeljb@umich.edu
e-mail: stein@umich.edu
e-mail: tersal@umich.edu
Development and Engineering Center,
e-mail: mark.j.brudnak.civ@mail.mil
e-mail: asalvi@umich.edu
e-mail: youngki@umich.edu
e-mail: siegeljb@umich.edu
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.
Ersal, T., Brudnak, M., Salvi, A., Kim, Y., Siegel, J. B., and Stein, J. L. (August 8, 2014). "An Iterative Learning Control Approach to Improving Fidelity in Internet-Distributed Hardware-in-the-Loop Simulation." ASME. J. Dyn. Sys., Meas., Control. November 2014; 136(6): 061012. https://doi.org/10.1115/1.4027868
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