Distributed fixed-time optimization for multi-agent systems via event-triggered intermittent communication

For the distributed optimization problem of multi-agent systems (MASs), this paper proposes a new event-triggered aperiodic intermittent communication control method and studies the fixed-time convergence of the MASs. Firstly, compared with existing distributed optimization problems, a more general one is considered in which the optimization objective is a convex combination of local objective functions. Secondly, to reduce the communication cost, a new event-triggered intermittent control protocol is designed. By introducing two auxiliary dynamical systems, and using fixed-time stability theory, algebraic graph theory and inequality techniques, it is proved that agents’ states can reach consensus in a fixed-time interval and asymptotically converge to the optimal solution of the optimization problem. In a combination with the event-triggering condition and intermittent control mechanism, Zeno behavior can be avoided. Finally, a numerical example is given to verify the effectiveness of the conclusion. © 2023 Northeast University. All rights reserved.