Paper Info
Title
A Hybrid Differential Dynamic Programming Algorithm for Constrained Optimal Control Problems. Part 1: Theory.
Abstract
A new algorithm is presented to solve constrained nonlinear optimal control problems, with an emphasis on highly nonlinear dynamical systems. The algorithm, called HDDP, is a hybrid variant of differential dynamic programming, a proven second-order technique that relies on Bellman’s Principle of Optimality and successive minimization of quadratic approximations. The new hybrid method incorporates nonlinear mathematical programming techniques to increase efficiency: quadratic programming subproblems are solved via trust region and range-space active set methods, an augmented Lagrangian cost function is utilized, and a multiphase structure is implemented. In addition, the algorithm decouples the optimization from the dynamics using first- and second-order state transition matrices. A comprehensive theoretical description of the algorithm is provided in this first part of the two paper series. Practical implementation and numerical evaluation of the algorithm is presented in Part 2.
Year
DOI
Venue
2012
10.1007/s10957-012-0039-0
J. Optimization Theory and Applications
Keywords
Field
DocType
Optimal control, Differential dynamic programming, Nonlinear optimization, Large-scale problem, Trust region, Augmented Lagrangian
Trust region,Optimal substructure,Mathematical optimization,Differential dynamic programming,Optimal control,Nonlinear programming,Algorithm,Augmented Lagrangian method,Quadratic programming,Criss-cross algorithm,Mathematics
Journal
Volume
Issue
ISSN
154
2
1573-2878
Citations 
PageRank 
References 
5
0.61
15
Authors
2
Name
Order
Citations
PageRank
Gregory Lantoine191.15
Ryan P. Russell291.15