Stochastic bounded consensus tracking of second-order multi-agent systems with measurement noises based on sampled-data with small sampling delay

Abstract

This paper is devoted to the stochastic bounded consensus tracking problems of second-order multi-agent systems, where the control input of each agent can only use the information measured at the sampling instants from its neighbors or the virtual leader with a time-varying reference state, the measurements are corrupted by random noises, and the signal sampling process induces the small sampling delay. The augmented matrix method, the probability limit theory and some other techniques are employed to derive the necessary and sufficient conditions guaranteeing the mean square bounded consensus tracking. We show that the convergence of the proposed protocol simultaneously depends on the constant feedback gains, the network topology, the sampled period and the sampling delay, and that the static consensus tracking error depends on not only the above mentioned factors, but also the noise intensity and the upper bound of the velocity and the acceleration of the virtual leader. The obtained results cover no sampling delay as its one special case. Simulations are provided to demonstrate the effectiveness of the theoretical results.