Optimization with an auxiliary constraint and decomposition
SIAM Journal on Control and Optimization
Convex Optimization
Design of optimal controllers for spatially invariant systems with finite communication speed
Automatica (Journal of IFAC)
Parallel and distributed vision algorithms using dual decomposition
Computer Vision and Image Understanding
Cooperative distributed MPC for tracking
Automatica (Journal of IFAC)
Decentralized-coordinated model predictive control for a hydro-power valley
Mathematics and Computers in Simulation
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We show how dynamic price mechanisms can be used for decomposition and distributed optimization of feedback systems. A classical method to handle large scale optimization problems is dual decomposition, where the coupling between sub-problems is relaxed using Lagrange multipliers. These variables can be interpreted as prices in a market mechanism serving to achieve mutual agreement between solutions of the sub-problems. In this paper, the same idea is used for decomposition of feedback systems, with dynamics in both decision variables and prices. We show how the prices can be used for a decentralized test, to verify that the global feedback system stays within a prespecified distance from optimality.