Modified quasilinearization algorithm for optimal control problems with nondifferential constraints and general boundary conditions

This paper considers the numerical solution of the problem of minimizing a functional I, subject to differential constraints, nondifferential constraints, and general boundary conditions. It consists of finding the state x(t), the control u(t), and the parameter pi so that the functional I is minimi...

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Bibliographic Details
Published inJournal of optimization theory and applications Vol. 50; no. 1; pp. 109 - 128
Main Authors Gonzalez, S., Rodriguez, S.
Format Journal Article
LanguageEnglish
Published New York, NY Springer 01.07.1986
Subjects
Applied sciences
Computer science; control theory; systems
Control theory. Systems
Exact sciences and technology
Optimal control
Numerical analysis
Constraint
Quasilinearization
Optimal control
Functional minimization
Variational calculus
Boundary condition
Algorithm
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Summary:This paper considers the numerical solution of the problem of minimizing a functional I, subject to differential constraints, nondifferential constraints, and general boundary conditions. It consists of finding the state x(t), the control u(t), and the parameter pi so that the functional I is minimized while the constraints are satisfied to a predetermined accuracy. The modified quasilinearization algorithm (MQA) is extended, so that it can be applied to the solution of optimal control problems with general boundary conditions, where the state is not explicitly given at the initial point. The algorithm presented here preserves the MQA descent property on the cumulative error.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0022-3239
1573-2878
DOI:10.1007/BF00938480