ACM Transactions on Mathematical Software· 2014Q1
GPOPS-II
- 1,316citations
- Q1SCImago
- 2014year
Short summary
GPOPS-II is a new MATLAB software that solves complex optimal control problems using a Legendre-Gauss-Radau collocation method, achieving specified accuracy via adaptive mesh refinement.
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Key points
- GPOPS-II solves multiple-phase optimal control problems using variable-order Gaussian quadrature collocation.
- It transcribes problems to nonlinear programming (NLP) problems via Legendre-Gauss-Radau collocation.
- Adaptive mesh refinement optimizes mesh intervals and polynomial degrees for accuracy.
- The software interfaces with quasi-Newton or Newton NLP solvers and uses sparse finite-differencing for derivatives.
AI-generated from the title and abstract; the full text is not read.
Abstract
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. The software employs a Legendre-Gauss-Radau quadrature orthogonal collocation method where the continuous-time optimal control problem is transcribed to a large sparse nonlinear programming problem (NLP). An adaptive mesh refinement method is implemented that determines the number of mesh intervals and the degree of the approximating polynomial within each mesh interval to achieve a specified accuracy. The software can be interfaced with either quasi-Newton (first derivative) or Newton (second derivative) NLP solvers, and all derivatives required by the NLP solver are approximated using sparse finite-differencing of the optimal control problem functions. The key components of the software are described in detail and the utility of the software is demonstrated on five optimal control problems of varying complexity. The software described in this article provides researchers a useful platform upon which to solve a wide variety of complex constrained optimal control problems.
The authors' abstract, as published at the source. ACM Transactions on Mathematical Software, 2014 · DOI ↗
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Field: Aerospace Engineering
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