Distributed Optimal Resource Allocation with Time-Varying Quadratic Cost Functions and Resources over Switching Agents

Esteki, Amir-Salar; Kia, Solmaz S.

doi:10.23919/ecc55457.2022.9838317

Cited by 4 publications

(1 citation statement)

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“…The computation of L-J ellipsoids can be posed as an optimization program [15]. In this sense, distributed optimization methods [22] have been intensively researched in recent years, where a general assumption [4], [9], [21], [25] is that the global cost function is the sum of local objectives. In the case of L-J methods, the cost function is not separable.…”

Section: Introductionmentioning

confidence: 99%

Distributed Outer Approximation of the Intersection of Ellipsoids

Aldana‐López

Sebastián

Aragüés

et al. 2023

IEEE Control Syst. Lett.

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The outer Löwner-John method is widely used in sensor fusion applications to find the smallest ellipsoid that can approximate the intersection of a set of ellipsoids, described by positive definite covariance matrices modeling the quality of each sensor. We propose a distributed algorithm to solve this problem when these matrices are defined over the network's nodes. This is of particular significance as it is the first decentralized algorithm capable of computing the covariance intersection ellipsoid by combining information from the entire network using only local interactions. The solution is based on a reformulation of the centralized problem, leading to a local protocol based on exact dynamic consensus tools. After reaching consensus, the protocol converges to an outer Löwner-John ellipsoid in finite time, and to the global optimum asymptotically. Formal convergence analysis and numerical experiments are provided to validate the proposal's advantages.

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