Agent-Supervisor Coordination for Decentralized Event-Triggered Optimization

Priyank Srivastava, Guido Cavraro, Jorge Cortes

Research output: Contribution to journalArticlepeer-review


This letter proposes decentralized resource-aware coordination schemes for solving network optimization problems defined by objective functions that combine locally evaluable costs with network-wide coupling components. These methods are well suited for a group of supervised agents trying to solve an optimization problem under mild coordination requirements. Each agent has information on its local cost and coordinates with the network supervisor for information about the coupling term of the cost. The proposed approach is feedback-based and asynchronous by design, guarantees anytime feasibility, and ensures the asymptotic convergence of the network state to the desired optimizer. Numerical simulations on a power system example illustrate our results.

Original languageAmerican English
Pages (from-to)1970-1975
Number of pages6
JournalIEEE Control Systems Letters
StatePublished - 2022

Bibliographical note

Publisher Copyright:
2475-1456 © 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See for more information.

NREL Publication Number

  • NREL/JA-5D00-81599


  • Convergence
  • Costs
  • Couplings
  • Government
  • Heuristic algorithms
  • Linear programming
  • Power system dynamics


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