
Charles Cao
· Assistant ProfessorVirginia Tech · Physics
Active 2000–2025
Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.
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 authorIn 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
NRI-Small: Cooperative Underwater Robotic Networks for Discovery & Rescue
NSF · $568k · 2012–2015
Frequent coauthors
- 119 shared
Naira Hovakimyan
- 28 shared
Enric Xargay
University of Michigan–Ann Arbor
- 24 shared
Isaac Kaminer
Naval Postgraduate School
- 24 shared
Vladimir Dobrokhodov
Naval Postgraduate School
- 24 shared
Irene M. Gregory
Langley Research Center
- 23 shared
Eugene Lavretsky
- 14 shared
Vijay Patel
Aeronautical Development Agency
- 13 shared
Jie Luo
Chinese Academy of Sciences
Labs
Center for Quantum Information Science and EngineeringPI
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