Distributed Fixed-Time Optimal Control of First-Order Stochastic Multi-Agent Systems

The present paper focuses on the distributed fixed-time optimization control issue within multi-agent systems under the influence of random noise interference. Through the introduction of a power-integral feedback distributed nonlinear optimal controller, along with the application of random Lyapunov stability theory and convex optimization techniques, it's guaranteed that even in the presence of random disturbances, the system can attain global convergence within a fixed time. The simulation results verify the accuracy of the theoretical outcomes.