Numerical methods for solving applied optimal control problems

For an optimal control problem with state constraints, an iterative solution method is described based on reduction to a finite-dimensional problem, followed by applying a successive linearization algorithm with the use of an augmented Lagrangian. The efficiency of taking into account state constrai...

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Bibliographic Details
Published in:Computational mathematics and mathematical physics Vol. 53; no. 12; pp. 1825 - 1838
Main Authors: Gornov, A. Yu, Tyatyushkin, A. I., Finkelstein, E. A.
Format: Journal Article
Language:English
Published: Boston Springer US 01.12.2013
Springer Nature B.V
Subjects:
Accuracy
Algorithms
Approximation
Computational mathematics
Computational Mathematics and Numerical Analysis
Control theory
Efficiency
Lagrange multiplier
Linear programming
Mathematical analysis
Mathematics
Mathematics and Statistics
Methods
Numerical analysis
Simplex method
Software
Studies
optimal control
augmented Lagrangian
iteration methods
state constraints
successive linearization
ISSN:0965-5425, 1555-6662
Online Access:Get full text
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Summary:For an optimal control problem with state constraints, an iterative solution method is described based on reduction to a finite-dimensional problem, followed by applying a successive linearization algorithm with the use of an augmented Lagrangian. The efficiency of taking into account state constraints in optimal control computation is illustrated by numerically solving several application problems.
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ISSN:0965-5425
1555-6662
DOI:10.1134/S0965542513120063