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Computation of approximate value functions for constrained control problems

Wernrud, Andreas LU (2006) 17th International Symposium on Mathematical Theory of Networks and Systems, 2006
Abstract
The paper discusses an iterative algorithm for computing approximations to the

optimal value function for constrained control problems. The algorithm gives an

explicit measure on the distance to the optimal value function. A major step

in the course of constructing an algorithm for these problems is to choose

an efficient parameterization. The choice has several implications.

The main obstacle in the algorithm we consider is that it involves an

infinite-dimensional optimization problem in each step, without

approximations these problems are computationally infeasible. The choice of

parameterization must thus be chosen accordingly. Multivariate polynomials... (More)
The paper discusses an iterative algorithm for computing approximations to the

optimal value function for constrained control problems. The algorithm gives an

explicit measure on the distance to the optimal value function. A major step

in the course of constructing an algorithm for these problems is to choose

an efficient parameterization. The choice has several implications.

The main obstacle in the algorithm we consider is that it involves an

infinite-dimensional optimization problem in each step, without

approximations these problems are computationally infeasible. The choice of

parameterization must thus be chosen accordingly. Multivariate polynomials

are a good candidate parameterization. To obtain a feasible algorithm, we

impose certain convexity properties and make use of recent results on

the representation of positive polynomials. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to conference
publication status
published
subject
keywords
Optimal Control, Dynamic Programming, Convex Optimization
conference name
17th International Symposium on Mathematical Theory of Networks and Systems, 2006
language
English
LU publication?
yes
id
f0eba919-046b-4a3f-9d70-8c26f09b629a (old id 945395)
date added to LUP
2008-01-23 11:47:22
date last changed
2016-06-21 16:01:00
@misc{f0eba919-046b-4a3f-9d70-8c26f09b629a,
  abstract     = {The paper discusses an iterative algorithm for computing approximations to the <br/><br>
optimal value function for constrained control problems. The algorithm gives an <br/><br>
explicit measure on the distance to the optimal value function. A major step <br/><br>
in the course of constructing an algorithm for these problems is to choose <br/><br>
an efficient parameterization. The choice has several implications. <br/><br>
The main obstacle in the algorithm we consider is that it involves an <br/><br>
infinite-dimensional optimization problem in each step, without <br/><br>
approximations these problems are computationally infeasible. The choice of <br/><br>
parameterization must thus be chosen accordingly. Multivariate polynomials <br/><br>
are a good candidate parameterization. To obtain a feasible algorithm, we <br/><br>
impose certain convexity properties and make use of recent results on <br/><br>
the representation of positive polynomials.},
  author       = {Wernrud, Andreas},
  keyword      = {Optimal Control,Dynamic Programming,Convex Optimization},
  language     = {eng},
  title        = {Computation of approximate value functions for constrained control problems},
  year         = {2006},
}