A multiobjective dynamic programming approach to constrained discrete-time optimal control

This paper presents a multiobjective differential dynamic programming approach to constrained discrete-time optimal control. In the backward sweep of the dynamic programming in the quadratic sub-problem, the sub-problem input at a stage or time step is solved in terms of the sub-problem state enteri...

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Published inProceedings of the 1998 American Control Conference. ACC (IEEE Cat. No.98CH36207) Vol. 5; pp. 3077 - 3083 vol.5
Main Authors Driessen, B.J., Kwok, K.S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1998
Subjects
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ISBN0780345304
9780780345300
ISSN0743-1619
DOI10.1109/ACC.1998.688424

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Abstract This paper presents a multiobjective differential dynamic programming approach to constrained discrete-time optimal control. In the backward sweep of the dynamic programming in the quadratic sub-problem, the sub-problem input at a stage or time step is solved in terms of the sub-problem state entering that stage so as to minimize the summed immediate and future cost subject to minimizing the summed immediate and future constraint violations, for all such entering states. The method differs from previous dynamic programming methods, which used penalty methods, in that the constraints of the sub-problem, which may include terminal constraints and path constraints, are solved exactly if they are solvable; otherwise, their total violation is minimized. Again, the resulting solution of the sub-problem is an input history that minimizes the quadratic cost function subject to being a minimizer of the total constraint violation. The expected quadratic convergence of the proposed algorithm is demonstrated on a numerical example.
AbstractList This paper presents a multiobjective differential dynamic programming approach to constrained discrete-time optimal control. In the backward sweep of the dynamic programming in the quadratic sub-problem, the sub-problem input at a stage or time step is solved in terms of the sub-problem state entering that stage so as to minimize the summed immediate and future cost subject to minimizing the summed immediate and future constraint violations, for all such entering states. The method differs from previous dynamic programming methods, which used penalty methods, in that the constraints of the sub-problem, which may include terminal constraints and path constraints, are solved exactly if they are solvable; otherwise, their total violation is minimized. Again, the resulting solution of the sub-problem is an input history that minimizes the quadratic cost function subject to being a minimizer of the total constraint violation. The expected quadratic convergence of the proposed algorithm is demonstrated on a numerical example.
Author Kwok, K.S.
Driessen, B.J.
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Snippet This paper presents a multiobjective differential dynamic programming approach to constrained discrete-time optimal control. In the backward sweep of the...
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StartPage 3077
SubjectTerms Convergence of numerical methods
Cost function
Dynamic programming
Heuristic algorithms
History
Iterative algorithms
Laboratories
Linear matrix inequalities
Optimal control
Time factors
Title A multiobjective dynamic programming approach to constrained discrete-time optimal control
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