论文部分内容阅读
This paper studies the consensus problems for a group of agents with switching topology and time-varying communication delays,where the dynamics of agents is modeled as a high-order integrator.A linear distributed consensus protocol is proposed,which only depends on the agent’s own information and its neighbors’partial information.By introducing a decomposition of the state vector and performing a state space transformation,the closed-loop dynamics of the multi-agent system is converted into two decoupled subsystems.Based on the decoupled subsystems,some sufficient conditions for the convergence to consensus are established,which provide the upper bounds on the admissible communication delays.Also,the explicit expression of the consensus state is derived.Moreover,the results on the consensus seeking of the group of high-order agents have been extended to a network of agents with dynamics modeled as a completely controllable linear time-invariant system.It is proved that the convergence to consensus of this network is equivalent to that of the group of high-order agents.Finally,some numerical examples are given to demonstrate the effectiveness of the main results.
This paper studies the consensus problems for a group of agents with switching topology and time-varying communication delays, where the dynamics of agents is modeled as a high-order integrator. A linear distributed consensus protocol is proposed, which only depends on the agent’s own information and its neighbors’ partial information. By introducing a decomposition of the state vector and performing a state space transformation, the closed-loop dynamics of the multi-agent system is converted into two decoupled subsystems. Based on the decoupled subsystems, some sufficient conditions for the convergence to consensus are established, which provide the upper bounds on the admissible communication delays. Als, the explicit expression of the consensus state is derived. Moreover, the results on the consensus seeking of the group of high-order agents have been extended to a network of agents with dynamics modeled as a completely controllable linear time-invariant system. It is proved that the convergence to consensus of this network is equivalent to that of the group of high-order agents. Finally, some numerical examples are to demonstrate the effectiveness of the main results.