LAUSR

The distributed optimal consensus based on an event-triggered scheme for Euler–Lagrange (EL) multiagent systems is investigated in this article. The objective is to minimize the global cost function in a distributed manner while achieving consensus, where the local cost function of each agent is only known by itself. First, the distributed optimization algorithms based on the event-triggered scheme are proposed to achieve optimal consensus as well as reduce communication costs for the EL multiagent systems when the model parameters are available. Second, when the model parameters are unavailable, the tracking controllers are developed to solve the optimization problem for the EL multiagent systems. Then, the distributed optimization problem for EL systems can be transformed into the tracking problem for double-integrator multiagent systems. With the proposed algorithms, global optimization can be achieved with the exponential convergence rate. Finally, a simulation example is presented to illustrate the effectiveness of the proposed method.