Event-Based Adaptive Consensus Control for Multiagent Systems With Asymmetric Multi-Information-Related Constraints on All States
针对全状态受非对称多信息相关约束的非线性多智能体系统，提出一种自适应事件触发跟踪控制方案，利用模糊逻辑系统处理未知项，通过积分障碍李雅普诺夫函数防止状态越界，并采用变阈值事件触发机制节省网络资源。
In this article, the problem of adaptive event-triggered tracking control is investigated for a class of nonlinear multiagent systems (MASs) with asymmetric multi-information-related (MIR) constraints on all states. The fuzzy-logic systems (FLSs) are utilized to model the system unknown items by virtue of their universal approximation properties. The appropriate integral barrier Lyapunov functions (IBLFs) are selected to prevent the states from exceeding the asymmetric constraint boundaries associated with multi-information, which include historical states, time and neighbor outputs. The event-triggered mechanism (ETM) with varying threshold is employed to reduce the update frequency of the controller, thereby achieving the purpose of saving network resources, including communication bandwidth and computation abilities. Under the backstepping technique framework, the required control scheme is designed by integrating the adaptive controller with triggering mechanism. And it is proven that the controlled plant with state constraint conditions is stable, the consensus tracking errors can eventually remain near the origin, and the Zeno behavior does not exist. Finally, the simulation results corroborate the view that the designed control scheme is effective.