10 research outputs found
Optimal Output Feedback Architecture for Triangular LQG Problems
Distributed control problems under some specific information constraints can
be formulated as (possibly infinite dimensional) convex optimization problems.
The underlying motivation of this work is to develop an understanding of the
optimal decision making architecture for such problems. In this paper, we
particularly focus on the N-player triangular LQG problems and show that the
optimal output feedback controllers have attractive state space realizations.
The optimal controller can be synthesized using a set of stabilizing solutions
to 2N linearly coupled algebraic Riccati equations, which turn out to be easily
solvable under reasonable assumptions.Comment: To be presented at 2014 American Control Conferenc
Optimal Decentralized State-Feedback Control with Sparsity and Delays
This work presents the solution to a class of decentralized linear quadratic
state-feedback control problems, in which the plant and controller must satisfy
the same combination of delay and sparsity constraints. Using a novel
decomposition of the noise history, the control problem is split into
independent subproblems that are solved using dynamic programming. The approach
presented herein both unifies and generalizes many existing results
Optimal Control for LQG Systems on Graphs---Part I: Structural Results
In this two-part paper, we identify a broad class of decentralized
output-feedback LQG systems for which the optimal control strategies have a
simple intuitive estimation structure and can be computed efficiently. Roughly,
we consider the class of systems for which the coupling of dynamics among
subsystems and the inter-controller communication is characterized by the same
directed graph. Furthermore, this graph is assumed to be a multitree, that is,
its transitive reduction can have at most one directed path connecting each
pair of nodes. In this first part, we derive sufficient statistics that may be
used to aggregate each controller's growing available information. Each
controller must estimate the states of the subsystems that it affects (its
descendants) as well as the subsystems that it observes (its ancestors). The
optimal control action for a controller is a linear function of the estimate it
computes as well as the estimates computed by all of its ancestors. Moreover,
these state estimates may be updated recursively, much like a Kalman filter
Dynamic programming solutions for decentralized state-feedback LQG problems with communication delays
This paper presents explicit solutions for a class of decentralized LQG problems in which players communicate their states with delays. A method for decomposing the Bellman equation into a hierarchy of independent subproblems is introduced. Using this decomposition, all of the gains for the optimal controller are computed from the solution of a single algebraic Riccati equation. © 2012 AACC American Automatic Control Council)
Dynamic Programming Solutions for Decentralized State-Feedback LQG Problems with Communication Delays
This paper presents explicit solutions for a class of decentralized LQG problems in which players communicate their states with delays. A method for decomposing the Bellman equation into a hierarchy of independent subproblems is introduced. Using this decomposition, all of the gains for the optimal controller are computed from the solution of a single algebraic Riccati equation