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Anil V. Rao
Researcher at University of Florida
Publications - 144
Citations - 7074
Anil V. Rao is an academic researcher from University of Florida. The author has contributed to research in topics: Optimal control & Orthogonal collocation. The author has an hindex of 35, co-authored 134 publications receiving 6126 citations. Previous affiliations of Anil V. Rao include Boston University & Charles Stark Draper Laboratory.
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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 +1 more
TL;DR: A general-purpose MATLAB software program called GPOPS--II is described for solving multiple-phase optimal control problems using variable-order Gaussian quadrature collocation methods.
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Brief paper: A unified framework for the numerical solution of optimal control problems using pseudospectral methods
Divya Garg,Michael A. Patterson,William W. Hager,Anil V. Rao,David Benson,Geoffrey T. Huntington +5 more
TL;DR: transformations are developed that relate the Lagrange multipliers of the discrete nonlinear programming problem to the costates of the continuous optimal control problem and the LGL costate approximation is found to have an error that oscillates about the true solution.
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Corrigendum: Algorithm 902: GPOPS, a MATLAB software for solving multiple-phase optimal control problems using the gauss pseudospectral method
Anil V. Rao,David Benson,Christopher L. Darby,Michael A. Patterson,Camila C. Francolin,Ilyssa Sanders,Geoffrey T. Huntington +6 more
TL;DR: An algorithm is described to solve multiple-phase optimal control problems using a recently developed numerical method called the Gauss pseudospectral method, well suited for use in modern vectorized programming languages such as FORTRAN 95 and MATLAB.
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Direct Trajectory Optimization and Costate Estimation via an Orthogonal Collocation Method
TL;DR: In this paper, a pseudospectral method for solving nonlinear optimal control problems is presented, where orthogonal collocation of the dynamics is performed at the Legendre-Gauss points.
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An hp‐adaptive pseudospectral method for solving optimal control problems
TL;DR: An hp‐adaptive pseudospectral method that iteratively determines the number of segments, the width of each segment, and the polynomial degree required in each segment in order to obtain a solution to a user‐specified accuracy.