Distributed Optimization for a Class of Nonlinear Multiagent Systems With Disturbance Rejection
针对一类受外部扰动的非线性多智能体系统，提出一种基于内模原理的分布式优化控制器，在实现最优一致性的同时抑制扰动，适用于连续时间最小相位系统。
The paper studies the distributed optimization problem for a class of nonlinear multiagent systems in the presence of external disturbances. To solve the problem, we need to achieve the optimal multiagent consensus based on local cost function information and neighboring information and meanwhile to reject local disturbance signals modeled by an exogenous system. With convex analysis and the internal model approach, we propose a distributed optimization controller for heterogeneous and nonlinear agents in the form of continuous-time minimum-phase systems with unity relative degree. We prove that the proposed design can solve the exact optimization problem with rejecting disturbances.