Distributed Cooperative Optimization for Nonlinear Heterogeneous MASs Under Intermittent Communication
Chao Deng, Lei Xu, Tao Yang, Dong Yue, Tianyou Chai
Abstract
In this article, we investigate the distributed cooperative optimization problem for heterogeneous uncertain high-order nonlinear multi-agent systems with an intermittent communication network, where each agent can only share information with its neighbors in some disjoint time intervals. To address this problem, the design process consists of constructing a distributed optimization algorithm and designing a decentralized tracking controller. To design a distributed optimization algorithm, virtual signals are constructed for all agents to minimize the cost function under the influence of the intermittent communication network. Based on the optimal virtual signals, local references with the existence of high-order derivatives are constructed by using the Hermite interpolation method. Then, a decentralized adaptive controller is designed for each local agent by following the recursive backstepping design procedure. It is theoretically shown that the distributed cooperative optimization problem is solved with the proposed method. Finally, a simulation example is introduced to verify the efficiency of the proposed method.