Liu, QingchenYe, BenQin, JiahuYu, Brad2023-09-081083-4419http://hdl.handle.net/1885/298843This paper proposes three different distributed event-triggered control algorithms to achieve leader-follower consensus for a network of Euler-Lagrange agents. We first propose two model-independent algorithms for a subclass of Euler-Lagrange agents without the vector of gravitational potential forces. By model-independent, we mean that each agent can execute its algorithm with no knowledge of the agent self-dynamics. A variable-gain algorithm is employed when the sensing graph is undirected; algorithm parameters are selected in a fully distributed manner with much greater flexibility compared to all previous work studying event-triggered consensus problems. When the sensing graph is directed, a constant-gain algorithm is employed. The control gains must be centrally designed to exceed several lower bounding inequalities, which require limited knowledge of bounds on the matrices describing the agent dynamics, bounds on network topology information, and bounds on the initial conditions. When the Euler-Lagrange agents have dynamics that include the vector of gravitational potential forces, an adaptive algorithm is proposed. This requires more information about the agent dynamics but allows for the estimation of uncertain parameters associated with the agent self-dynamics. For each algorithm, a trigger function is proposed to govern the event update times. The controller is only updated at each event, which ensures that the control input is piecewise constant and thus saves energy resources. We analyze each controller and trigger function to exclude Zeno behavior.The work of Q. Liu was supported in part by the Australian Research Council under Grant DP-130103610 and Grant DP160104500, in part by the National Natural Science Foundation of China under Grant 61375072, and in part by the China Scholarship Council Ph.D. Scholarship. The work of M. Ye was supported in part by the Australian Research Council under Grant DP-130103610 and Grant DP-160104500, in part by the National Natural Science Foundation of China under Grant 61375072, and in part by the Australian Government Research Training Program Scholarship. The work of J. Qin was supported in part by the National Natural Science Foundation of China under Grant 61473269, and in part by the Youth Innovation Promotion Association of Chinese Academy of Sciences. The work of C. Yu was supported in part by the Australian Research Council under Grant DP-130103610 and Grant DP-160104500, and in part by the National Natural Science Foundation of China under Grant 61375072application/pdfen-AU© 2017 IEEE.Euler–Lagrange dynamicsevent-based controlleader–follower consensusmultiagent systems201910.1109/TSMC.2017.27728202022-07-24