In this paper, we study the problems of event-based communication and actuation algorithms to mitigate unnecessary network burden and energy consumption, hence increasing the number and work time of robots/agents in a network of multi-agent systems. By considering the general dynamic model of networked Euler-Lagrange systems and utilizing the adaptive control algorithm, we propose two event-triggered schemes, an event-based communication, and an event-based controller for a large number of agents to achieve consensus in the task space. Assuming that the network connection is directed spanning tree and the time-varying communication delays are bounded. Theoretical analyses of the proposed control algorithms for both leaderless and leader-follower (static leader) consensus are studied by employing the Lyapunov technique and function analysis. It revealed that the network achieved global stability and asymptotical convergence with avoidance of Zeno behavior. We experimented with a system of four robotic manipulators and performed numerical simulations for a networked mobile manipulator to demonstrate the efficiency and efficacy of the proposed consensus algorithms.
All Science Journal Classification (ASJC) codes