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Gradient methods for iterative distributed control synthesis

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Author

Summary, in English

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.

Publishing year

2009

Language

English

Document type

Conference paper

Topic

  • Control Engineering

Conference name

48th IEEE Conference on Decision and Control

Conference date

2009-12-16

Conference place

Shanghai, China

Status

Published

Research group

  • LCCC