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Charles Cao

Charles Cao

· Assistant Professor

Virginia Tech · Physics

Active 2000–2025

h-index35
Citations5.4k
Papers2049 last 5y
Funding$568k

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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About

Charles Cao is an Assistant Professor in the Department of Physics at Virginia Tech, located in the Center for Quantum Information Science and Engineering. His research focuses on Theoretical Condensed Matter Physics and String Theory. He holds a Ph.D. from the California Institute of Technology. His work involves exploring fundamental aspects of condensed matter systems and string theoretical frameworks, contributing to the understanding of complex physical phenomena. He is based at the Virginia Tech campus in Blacksburg, VA, and can be contacted via email at cjcao@vt.edu.

Research topics

  • Computer Science
  • Artificial Intelligence
  • Engineering
  • Mathematics
  • Control engineering
  • Mathematical optimization

Selected publications

  • L1-Adaptive MPPI Architecture for Robust and Agile Control of Multirotors

    arXiv (Cornell University) · 2020 · 21 citations

    This paper presents a multirotor control architecture, where Model Predictive Path Integral Control (MPPI) and L1 adaptive control are combined to achieve both fast model predictive trajectory planning and robust trajectory tracking. MPPI provides a framework to solve nonlinear MPC with complex cost functions in real-time. However, it often lacks robustness, especially when the simulated dynamics are different from the true dynamics. We show that the L1 adaptive controller robustifies the archit…

  • Robust Adaptive Control of Linear Parameter-Varying Systems with Unmatched Uncertainties

    arXiv (Cornell University) · 2020-10-09 · 5 citations

    preprintOpen accessSenior author

    In controlling systems with large operating envelopes, it is often necessary to adjust the desired dynamics according to operating conditions. This paper presents a robust adaptive control architecture for linear parameter-varying (LPV) systems that allows for the desired dynamics to be systematically scheduled, while being able to handle a broad class of uncertainties, both matched and unmatched, which can depend on both time and states. The proposed controller adopts an L1 adaptive control arc…

Recent grants

Frequent coauthors

  • Naira Hovakimyan

    119 shared
  • Enric Xargay

    University of Michigan–Ann Arbor

    28 shared
  • Isaac Kaminer

    Naval Postgraduate School

    24 shared
  • Vladimir Dobrokhodov

    Naval Postgraduate School

    24 shared
  • Irene M. Gregory

    Langley Research Center

    24 shared
  • Eugene Lavretsky

    23 shared
  • Vijay Patel

    Aeronautical Development Agency

    14 shared
  • Jie Luo

    Chinese Academy of Sciences

    13 shared

Labs

  • Center for Quantum Information Science and EngineeringPI

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