Average Consensus Of Multi-agent Systems Research Articles

Event-triggered average consensus for multi-agent systems with nonlinear dynamics and switching topology

The average consensus problem for a multi-agent system with nonlinear dynamics is studied in this paper by employing a distributed event-triggered control strategy. The strategy uses a piecewise continuous control law and an event-triggering function to control the system. The piecewise continuous control law only updates at infrequent instants and keeps steady at the previous value in the period between two instants. The event-triggering function determines these instants based on the state information of the agents at current and previous instants. This control approach is first applied to a first-order system under a connected topology in a centralized pattern. Then the switching topology case is considered. At last, both the first-order and the second-order system are considered under distributed event-triggered strategy. The distributed event-triggering function, which only employs the information of the corresponding agent and the states of its neighbors, is designed for each agent in the system. By utilizing Lyapunov method and graph theory, it is proven that the systems can reach consensus by using the event-triggered control strategy. Numerical examples are provided to show the efficacy of the proposed control strategy.

Event-Triggered Average Consensus for Multiagent Systems with Time-Varying Delay

The paper investigates average consensus for multiagent systems with time-varying delay. A reducing dimension multiagent systems model is presented firstly. Using event-triggered mechanism to reduce network load, a comprehensive model is then proposed, which considers communication delay and triggered issue. Furthermore, the event-triggered average consensus stability of multiagent systems with fixed directed/undirected graph is analyzed, and sufficient conditions are provided. Moreover, the upper bound of time-varying delay can be obtained conveniently. Finally, simulation results confirm the feasibility and effectiveness of the proposed method.

Average Consensus in Multiagent Systems with the Problem of Packet Losses When Using the Second-Order Neighbors’ Information

This paper mainly investigates the average consensus of multiagent systems with the problem of packet losses when both the first-order neighbors’ information and the second-order neighbors’ information are used. The problem is formulated under the sampled-data framework by discretizing the first-order agent dynamics with a zero-order hold. The communication graph is undirected and the loss of data across each communication link occurs at certain probability, which is governed by a Bernoulli process. It is found that the distributed average consensus speeds up by using the second-order neighbors’ information when packets are lost. Numerical examples are given to demonstrate the effectiveness of the proposed methods.

Mean square average-consensus for multi-agent systems with measurement noise and time delay

Mean square average consensus for multi-agent systems with measurement noise and time delay under fixed digraph is studied in this article. The time-varying consensus-gain is introduced to attenuate the measurement noise. By combining the tools of algebraic graph theory, matrix theory and stochastic analysis, consensus protocols for multi-agent systems with measurement noise and time delay are elaborately analysed. The example and simulation results are given to illustrate the effectiveness of the obtained theoretical results. Moreover, the simulations demonstrate that, the proper consensus-gain function in the consensus protocol is the necessary and sufficient condition for the convergence of the multi-agent systems.

Average consensus of multi-agent systems with communication time delays and noisy links

In this paper, we consider the average-consensus problem with communication time delays and noisy links. We analyze two different cases of coupling topologies: fixed and switching topologies. By utilizing the stability theory of the stochastic differential equations, we analytically show that the average consensus could be achieved almost surely with the perturbation of noise and the communication time delays even if the time delay is time-varying. The theoretical results show that multi-agent systems can tolerate relatively large time delays if the noise is weak, and they can tolerate relatively strong noise if the time delays are low. The simulation results show that systems with strong noise intensities yield slow convergence.