Distributed Optimization for Multiply High-Order Nonlinear Local Cost Functions

Shengshuai Wu, Yu Zhao
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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.
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多重高阶非线性局部代价函数的分布优化
研究了具有多个高阶liplic型非线性局部代价函数的多智能体系统的分布式优化问题。多智能体系统的目标是实现由局部性能函数之和构成的团队性能函数的最小化,其中每个局部目标函数只有一个智能体知道。然后提出了一种新的分布式优化算法,并通过Lyapunov稳定性和优化分析保证了算法的渐近收敛性。
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