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This paper investigates an optimal consensus problem for a group of uncertain linear multi-agent systems. All agents are allowed to possess parametric uncertainties that range over an arbitrarily large compact set. The goal is to collectively minimize a sum of local costs in a distributed fashion and finally achieve an output consensus on this optimal point using only output information of agents. By adding an optimal signal generator to generate the global optimal point, we convert this problem to several decentralized robust tracking problems. Output feedback integral control is constructively given to achieve an optimal consensus under a mild graph connectivity condition. The efficacy of this control is verified by a numerical example.
In this paper, an optimal output consensus problem is studied for discrete-time linear multiagent systems subject to external disturbances. Each agent is assigned with a local cost function which is known only to itself. Distributed protocols are to
In this paper we propose a novel method to establish stability and, in addition, convergence to a consensus state for a class of discrete-time Multi-Agent System (MAS) evolving according to nonlinear heterogeneous local interaction rules which is not
This study considers the problem of periodic event-triggered (PET) cooperative output regulation for a class of linear multi-agent systems. The advantage of the PET output regulation is that the data transmission and triggered condition are only need
In this paper, we consider scalable output and regulated output synchronization problems for heterogeneous networks of right-invertible linear agents based on localized information exchange where in the case of regulated output synchronization, the r
In this paper, a distributed learning leader-follower consensus protocol based on Gaussian process regression for a class of nonlinear multi-agent systems with unknown dynamics is designed. We propose a distributed learning approach to predict the re