Distributed Optimization for Multiply High-Order Nonlinear Local Cost Functions

Abstract

The distributed optimization problem of multi-agent system with multiple high-order Lipschiz-type nonlinear local cost functions is studied in this brief. The objective is for a multi-agent system to achieve the goal of minimizing team performance function formed by the sum of local performance functions where each local objective function is known to only one agent. Then a new distributed optimization algorithm is proposed, and the asymptotical convergence is guaranteed through the Lyapunov stability and optimization analysis.