World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
37
Citations
8981
World Ranking
5026
National Ranking
1746

Overview

Anil V. Rao is affiliated with the University of Florida in the United States. Their research work primarily spans the field of Engineering, with a strong focus on Aerospace Engineering and several related subfields. The scientist's publications cover a broad spectrum of topics within this domain.

Rao's main fields of study include Aerospace Engineering, Astronomy and Astrophysics, Applied Mathematics, Control and Systems Engineering, and Computational Mechanics. These areas form the foundation of their extensive research activity.

Their primary research topics include:

  • Spacecraft Dynamics and Control
  • Aerospace Engineering and Control Systems
  • Gas Dynamics and Kinetic Theory
  • Astro and Planetary Science
  • Space Satellite Systems and Control
  • Guidance and Control Systems
  • Computational Fluid Dynamics and Aerodynamics

Rao has coauthored multiple papers with several frequent collaborators, including Alexander T. Miller, Elisha R. Pager, Brittanny V. Holden, Mrinal Kumar, and William W. Hager. These collaborations have contributed to a sustained presence in aerospace and control systems research.

Most of Rao's publications appear in a diverse set of venues. The frequent publication venues include:

  • arXiv (Cornell University)
  • Journal of Spacecraft and Rockets
  • AIAA SCITECH 2022 Forum
  • AIAA Scitech 2020 Forum
  • Optimal Control Applications and Methods

Significant recent papers authored or coauthored by Rao encompass various aspects of optimal control, computational methods, and wireless communications. Selected works are:

  • "Learning Link Schedules in Self-Backhauled Millimeter Wave Cellular Networks," 2020, IEEE Transactions on Wireless Communications
  • "CGPOPS," 2020, ACM Transactions on Mathematical Software
  • "Method for solving chance constrained optimal control problems using biased kernel density estimators," 2020, Optimal Control Applications and Methods
  • "Modified Legendre-Gauss-Radau Collocation Method for Optimal Control Problems with Nonsmooth Solutions," 2021, Journal of Optimization Theory and Applications
  • "Method for solving bang-bang and singular optimal control problems using adaptive Radau collocation," 2022, Computational Optimization and Applications

The body of work reflects an emphasis on computational optimization and advanced control techniques, particularly applied to aerospace systems and related fields. The consistent production of scholarly articles and conference papers underscores a focus on both theoretical and applied aspects of engineering and applied mathematics.

Best Publications

  • GPOPS-II: A MATLAB Software for Solving Multiple-Phase Optimal Control Problems Using hp-Adaptive Gaussian Quadrature Collocation Methods and Sparse Nonlinear Programming

    Michael A. Patterson;Anil V. Rao

  • Brief paper: A unified framework for the numerical solution of optimal control problems using pseudospectral methods

    Divya Garg;Michael Patterson;William W. Hager;Anil V. Rao

  • Direct Trajectory Optimization and Costate Estimation via an Orthogonal Collocation Method

    David A. Benson;Geoffrey T. Huntington;Tom P. Thorvaldsen;Anil V. Rao

  • Corrigendum: Algorithm 902: GPOPS, a MATLAB software for solving multiple-phase optimal control problems using the gauss pseudospectral method

    Anil V. Rao;David A. Benson;Christopher Darby;Michael A. Patterson

  • An hp‐adaptive pseudospectral method for solving optimal control problems

    Christopher L. Darby;William W. Hager;Anil V. Rao

  • Brief paper: Pseudospectral methods for solving infinite-horizon optimal control problems

    Divya Garg;William W. Hager;Anil V. Rao

  • Direct trajectory optimization and costate estimation of finite-horizon and infinite-horizon optimal control problems using a Radau pseudospectral method

    Divya Garg;Michael A. Patterson;Camila Francolin;Christopher L. Darby

  • Evaluation of Direct Collocation Optimal Control Problem Formulations for Solving the Muscle Redundancy Problem

    Friedl De Groote;Allison L. Kinney;Anil V. Rao;Benjamin J. Fregly

  • Direct Trajectory Optimization Using a Variable Low-Order Adaptive Pseudospectral Method

    Christopher L. Darby;William W. Hager;Anil V. Rao

  • Optimal Reconfiguration of Spacecraft Formations Using the Gauss Pseudospectral Method

    Geoffrey T. Huntington;Anil V. Rao

  • A ph mesh refinement method for optimal control

    Michael A. Patterson;William W. Hager;Anil V. Rao

  • ENTRY TRAJECTORY TRACKING LAW VIA FEEDBACK LINEARIZATION

    Sanjay Bharadwaj;Anil V. Rao;Kenneth D. Mease

  • Exploiting Sparsity in Direct Collocation Pseudospectral Methods for Solving Optimal Control Problems

    Michael A. Patterson;Anil V. Rao

  • Adaptive mesh refinement method for optimal control using nonsmoothness detection and mesh size reduction

    Fengjin Liu;William W. Hager;Anil V. Rao

  • Muscle Synergies Facilitate Computational Prediction of Subject-Specific Walking Motions.

    Andrew J. Meyer;Ilan Eskinazi;Jennifer N. Jackson;Anil V. Rao

  • A Comparison of Accuracy and Computational Efficiency of Three Pseudospectral Methods

    Geoffrey Huntington;David Benson;Anil Rao

  • Optimal control of Formula One car energy recovery systems

    David J. N. Limebeer;Giacomo Perantoni;Anil V. Rao

  • Minimum-Time Trajectory Optimization of Low-Thrust Earth-Orbit Transfers with Eclipsing

    Kathryn F. Graham;Anil V. Rao

  • AN OVERVIEW OF THREE PSEUDOSPECTRAL METHODS FOR THE NUMERICAL SOLUTION OF OPTIMAL CONTROL PROBLEMS

    Divya Garg;Michael A. Patterson;William W. Hager;Anil V. Rao

  • Adaptive Mesh Refinement Method for Optimal Control Using Decay Rates of Legendre Polynomial Coefficients

    Fengjin Liu;William W. Hager;Anil V. Rao

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