In this paper, we consider a distributed time-varying formation and optimization problem for a group of robots with uncertain Euler-Lagrange dynamics. The robots are required to keep a time-varying formation as well as optimizing a quadratic objective function that is composed of the state information of all the robots. The problem is first mathematically reformulated as a distributed time-varying optimization problem, where the time-varying formation task is viewed as a time-varying constraint. An inexact penalty function based method is proposed to estimate the optimal solution of the time-varying optimization problem. Lyapunov based analysis is developed, and asymptotical convergence to the estimated optimal solution is proven. A numerical example is provided to show the effectiveness and efficiency of the proposed methods.
Piaoyi SuJianglong YuYongzhao HuaQingdong LiXiwang DongZhang Ren
Jingyao WangJialu DuJunnan LiuFrank L. Lewis
Justin R. KlotzSerhat ObuzZhen KanWarren E. Dixon