Huang Yi, Meng Ziyang
IEEE Trans Cybern. 2022 Sep;52(9):9120-9131. doi: 10.1109/TCYB.2021.3057426. Epub 2022 Aug 18.
This article studies a fully distributed optimal coordinated control problem with the global cost function for networked Euler-Lagrange (EL) systems subject to unknown model parameters. In particular, the global cost function is the sum of all the local cost functions assigned to each agent and only available to itself. The objective is to minimize the global cost function in a distributed manner while achieving a consensus on its optimal solution. Since the model parameters of the considered EL systems are not available, a new auxiliary system is introduced as a reference model, and its outputs exponentially converge the optimal solution of the global cost function. A fully distributed optimal control algorithm without requiring global information is first proposed. Then, an alternative distributed optimal algorithm via the event-triggered mechanism is proposed to reduce the communication cost. In particular, by combining an edge-based adaptive gain method, the proposed event-triggered optimal algorithm is also fully distributed. Finally, numerical simulation is carried out to validate the theoretical results.
本文研究了具有全局成本函数的网络化欧拉-拉格朗日（EL）系统的完全分布式最优协调控制问题，该系统存在未知模型参数。具体而言，全局成本函数是分配给每个智能体的所有局部成本函数之和，且仅对自身可用。目标是以分布式方式最小化全局成本函数，同时在其最优解上达成共识。由于所考虑的EL系统的模型参数不可用，引入了一个新的辅助系统作为参考模型，其输出以指数方式收敛到全局成本函数的最优解。首先提出了一种无需全局信息的完全分布式最优控制算法。然后，提出了一种基于事件触发机制的分布式最优算法，以降低通信成本。特别是，通过结合基于边的自适应增益方法，所提出的事件触发最优算法也是完全分布式的。最后，进行了数值模拟以验证理论结果。
