CGPOPS: A C plus plus Software for Solving Multiple-Phase Optimal Control Problems Using Adaptive Gaussian Quadrature Collocation and Sparse Nonlinear Programming

被引:18
作者
Agamawi, Yunus M. [1 ]
Rao, Anil, V [1 ]
机构
[1] Univ Florida, Aerosp & Mech Engn, Gainesville, FL 32611 USA
来源
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE | 2020年 / 46卷 / 03期
基金
美国国家科学基金会;
关键词
Optimal control; direct orthogonal collocation; Gaussian quadrature; hp methods; numerical methods; C plus; scientific computation; applied mathematics; FINITE-ELEMENT-METHOD; H-P-VERSION; DIRECT TRAJECTORY OPTIMIZATION; MESH REFINEMENT METHOD; PSEUDOSPECTRAL METHODS; CONVERGENCE RATE; COSTATE ESTIMATION; 1-DIMENSION; ALGORITHM; RATES;
D O I
10.1145/3390463
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
A general-purpose C++ software program called CGPOPS is described for solving multiple-phase optimal control problems using adaptive direct orthogonal collocation methods. The software employs a Legendre-Gauss-Radau direct orthogonal collocation method to transcribe the continuous optimal control problem into a large sparse nonlinear programming problem (NLP). A class of hp mesh refinement methods are implemented that determine the number of mesh intervals and the degree of the approximating polynomial within each mesh interval to achieve a specified accuracy tolerance. The software is interfaced with the open source Newton NLP solver IPOPT. All derivatives required by the NLP solver are computed via central finite differencing, bicomplex-step derivative approximations, hyper-dual derivative approximations, or automatic differentiation. 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 transitional platform to solve a wide variety of complex constrained optimal control problems.
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收藏
页数:38
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