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Gradient methods for iterative distributed control synthesis

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2 Author(s)
Karl MÃ¥rtensson ; Automatic Control LTH, Lund University, Box 118, SE-221 00 Sweden ; Anders Rantzer

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.

Published in:

Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on

Date of Conference:

15-18 Dec. 2009