Distributed fixed-time optimization for multiple second-order systems under directed communication topology
This article investigates the distributed optimization problem of second-order multi-agent systems under directed communication topologies,and proposes a distributed control algorithm for fixed-time convergence.The control algorithm is based on a novel distributed estimator design,enabling each intelligent agent to accurately estimate the gradient of the global objective function through local information exchange.Building upon the estimator,a distributed algorithm with fixed convergence time is devised for each intelligent agent,ensuring that all entities converge to the optimal solution of the objective function within a finite time.The stability of the algorithm is theoretically proven using fixed-time convergence theory and inequality scaling techniques,and the effectiveness of the proposed algorithm is demonstrated through numerical simulations.
second-order systemsfixed-time convergencedistributed optimizationdirected communication topologyconsensusgradient observer
万方数据
维普
