Digital Implementation of Derivative-Dependent Control by Using Delays for Stochastic Multiagents

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 nth-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.

Automated summary

This article investigates the digital implementation of derivative-dependent control for consensus of stochastic multiagent systems, approximating consensus controllers that rely on output and its derivatives as delayed sampled-data controllers. Novel Lyapunov functionals are proposed for consensus analysis to derive linear matrix inequalities for finding an acceptable sampling period, with efficiency demonstrated through numerical examples.