LAUSR

In this article, we study the digital implementation of derivative-dependent control for consensus of stochastic multiagent systems. The consensus controllers that depend on the output and its derivatives are approximated as delayed sampled-data controllers. First, we consider the $n$th-order stochastic multiagent systems. Second, we consider PID control of the second-order stochastic multiagent systems. For the consensus analysis, we propose novel Lyapunov functionals to derive linear matrix inequalities that allow us to find an admissible sampling period. The efficiency of the presented approach is illustrated by numerical examples.