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Gradient methods for iterative distributed control synthesis

Mårtensson, Karl LU and Rantzer, Anders LU (2009) 48th IEEE Conference on Decision and Control
Abstract
In this paper we present a gradient method to iteratively update local controllers of a distributed linear system driven by stochastic disturbances. The control objective is to minimize the sum of the variances of states and inputs in all nodes. We show that the gradients of this objective can be estimated distributively using data from a forward simulation of the system model and a backward simulation of the adjoint equations. Iterative updates of local controllers using the gradient estimates gives convergence towards a locally optimal distributed controller.
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organization
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type
Contribution to conference
publication status
published
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conference name
48th IEEE Conference on Decision and Control
external identifiers
  • Scopus:77950833465
language
English
LU publication?
yes
id
5b45d558-f1f4-45e7-9a5d-faa2f0a48d17 (old id 1626834)
date added to LUP
2010-07-02 09:06:57
date last changed
2016-10-13 04:55:31
@misc{5b45d558-f1f4-45e7-9a5d-faa2f0a48d17,
  abstract     = {In this paper we present a gradient method to iteratively update local controllers of a distributed linear system driven by stochastic disturbances. The control objective is to minimize the sum of the variances of states and inputs in all nodes. We show that the gradients of this objective can be estimated distributively using data from a forward simulation of the system model and a backward simulation of the adjoint equations. Iterative updates of local controllers using the gradient estimates gives convergence towards a locally optimal distributed controller.},
  author       = {Mårtensson, Karl and Rantzer, Anders},
  language     = {eng},
  title        = {Gradient methods for iterative distributed control synthesis},
  year         = {2009},
}