A Novel Sampled-Data Control for Reachable Set Estimation of Nonlinear Multiagent Systems
针对具有Lipschitz非线性和有界输入扰动的无领导多智能体系统，提出一种新颖的时变采样数据控制方法，通过构建不连续Lyapunov泛函和线性矩阵不等式条件，实现可达集估计，数值例子表明该方法能扩大采样周期并减少决策变量。
This article examines the reachable set estimation problem for leaderless multiagent systems (MASs) with Lipschitz nonlinear dynamics and bounded input disturbances via novel sampled-data control. First, a new time-dependent sampled-data control technique is proposed for nonlinear MASs. In contrast to the conventional approach, the developed control signal includes a sampling-time variable that varies over time within each sampling period. Next, the primary Lyapunov term consists of aperiodic sampling in various degrees, hence becoming discontinuous. Furthermore, sufficient reachable set conditions are derived as linear matrix inequalities by making use of Wirtinger’s inequality-based time-dependent discontinuous Lyapunov-Krasovskii functional and two-sided looped functional. In the end, two illustrated numerical examples validate theoretical outcomes exhibiting reduced conservatism by expanding the sampling period and minimizing the number of decision variables.