Fixed-Time Distributed Optimization for Multi-Agent Systems with Input Delays and External Disturbances

This study concentrates on a fixed-time distributed optimization problem for multi-agent systems (MASs) with input delay and external disturbances. First, by adopting the Artstein model reduction technique, time-delay system is first transformed into delay-free one, disturbances are then effectively eliminated using an integral sliding mode control strategy. Second, new centralized mechanism developed that allows all agents to reach same state in fixed time converge optimal value of global objective function. Meanwhile, extended switching topologies. Moreover, as gradient information function difficult obtain advance, we construct decentralized protocol enables acquire certain amount while also optimizing problem. Finally, two numerical simulations presented validate effectiveness reliability