1st-Order Dynamics on Nonlinear Agents for Resource Allocation over Uniformly-Connected Networks

Mohammadreza Doostmohammadian, Alireza Aghasi, Maria Vrakopoulou, Themistoklis Charalambous

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

5 Citations (Scopus)


A general nonlinear 1st-order consensus-based solution for distributed constrained convex optimization is proposed with network resource allocation applications. The solution is used to optimize continuously-differentiable strictly convex cost functions over weakly-connected undirected net-works, while it is anytime feasible and models various non-linearities to account for imperfections and constraints on the (physical model of) agents in terms of limited actuation capa-bilities, e.g., quantization and saturation. Due to such inherent nonlinearities, the existing linear solutions considering ideal agent models may not necessarily converge with guaranteed optimality and anytime feasibility. Some applications also im-pose specific nonlinearities, e.g., convergence in fixed/finite-time or sign-based robust disturbance-tolerant dynamics. Our pro-posed distributed protocol generalizes such nonlinear models. Putting convex set analysis together with nonsmooth Lyapunov analysis, we prove convergence, (i) regardless of the particular type of nonlinearity, and (ii) with weak network-connectivity requirements (uniform-connectivity).

Original languageEnglish
Title of host publication2022 IEEE Conference on Control Technology and Applications, CCTA 2022
Number of pages6
ISBN (Electronic)978-1-6654-7338-5
Publication statusPublished - 2022
MoE publication typeA4 Conference publication
EventIEEE Conference on Control Technology and Applications - Trieste, Italy
Duration: 23 Aug 202225 Aug 2022

Publication series

NameProceedings, Control Technology and Applications
ISSN (Print)2768-0762
ISSN (Electronic)2768-0770


ConferenceIEEE Conference on Control Technology and Applications
Abbreviated titleCCTA


  • convex optimization
  • graph theory
  • Network resource allocation
  • spanning tree


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  • FinEst Twins: FinEst Twins

    Nieminen, M.


    Project: EU: Framework programmes funding

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