Fully Distributed Leader-Following Consensus of Nonlinear Multiagent Systems: An Output-Dependent Dynamic Gain Method
针对有向图下高阶非线性多智能体系统，提出一种完全分布式输出反馈一致性协议，仅需父智能体三个变量信息，无需全局信息，能保证全局状态一致且误差渐近收敛。
This article addresses the fully distributed (FD) output feedback full states consensus tracking problem for high-order multiagent systems with general nonlinearities under the directed graph. In each agent, a novel FD estimator is established to estimate the leader’s states, which only needs three variables’ information from each parent agent without considering their orders. Meanwhile, it is independent of the graph’s scale and does not rely on any global information. Then, instead of the backstepping method and based on the constructed compensator, an output-dependent dynamic gain method is used to design the FD output feedback protocol avoiding the repeated derivatives of the nonlinearities. Based on a new lemma, it is proved that using the proposed FD protocol, global full states consensus stability can be guaranteed and the consensus error can converge to zero asymptotically. The proposed method can not only achieve the consensus in FD fashion but also extremely relax the conditions on nonlinearities which satisfy the local Lipschitz condition with a more general incremental rate containing output and compensator states information. Finally, a numerical example is given to verify the effectiveness of the proposed method.