Agent-Supervisor Coordination for Decentralized Event-Triggered Optimization

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