Abstract
This paper investigates the problem of the time-varying formation control of a second-order dynamic agent based on a distributed dynamic event-triggered algorithm. In this problem, each agent can exchange the information of its position and velocity with its neighbors via limited communication ability. Our approach provides a new dynamic event triggering mechanism to reduce the number of triggering times while maintaining satisfactory control performance. Further, a novel Lyapunov function is proposed to guarantee that the group of agents asymptotically tracks the desired time-varying formation trajectory. The practical applicability of the event triggering mechanism is also indicated by excluding the Zeno behavior in the proposed control algorithm. Finally, the validity and effectiveness of the proposed method are demonstrated via illustrative examples of the time-varying formation flight for six quadcopters.
Highlights
One of the most common animal habits that efficiently yields undeniable outcomes in nature is cooperative work
Motivated by the above observations, this paper proposes a dynamic event-triggered control algorithm for the time-varying formation of multi-agent systems
This section proposes a distributed dynamic event-triggered control law for each agent such that it achieves the predefined formation of the multi-agent system and avoids the continuous exchange of information among agents and the Zeno behavior
Summary
One of the most common animal habits that efficiently yields undeniable outcomes in nature is cooperative work. By considering an agent as a leader, second-order MASs that used event-sampling schemes achieved a consensus problem based on a leader-follower protocol in [27] These existing results somehow can be enriched by expanding with the time-varying formation control of multi-agent systems. Motivated by the above observations, this paper proposes a dynamic event-triggered control algorithm for the time-varying formation of multi-agent systems. It is worth noting that the control inputs depend on the states of the agent, and the desired formation trajectory, which makes our approach different from the existing approaches reported in [16,17,24,25,26] In this context, our approach ensures the exclusion of the Zeno behavior to avoid the accumulation of triggering instants as time goes to infinity.
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