Estimating uncertainties in cooperative networks

The cooperative output regulation problem has attracted considerable attention due to its wide applications in several real life problems; in the past decade, the cooperative control of multi-agent systems has become a trendy topic in the control community.In the cooperative output regulation problem the main purpose consists in achieving reference tracking and disturbance rejection.State-of-the-art methodologies can solve cooperative output regulation only by assuming some critical a priori knowledge: either the exosystem dynamics (e.g. their harmonic frequencies) can be globally shared; or some structural parameters of the communication graph (e.g. structural eigenvalues) are known; or initial stabilizing controllers are available for each system.However, from a practical point of view, it is crucial to develop adaptive methodologies to effectivelyhandle uncertainty in cooperative control of network systems, exploiting as little a priori information as possible.This work addresses and solves the cooperative output regulation problem without exploiting any of the aforementioned critical knowledge.In fact, the distinguishing feature of the proposed solution is to assume an uncertain cooperative scenario where neither follower nor leader dynamics are globally known. In particular, the exosystem dynamics are assumed to correspond to harmonic oscillators with unknown frequencies.Cooperative output regulation is achieved by designing, for each system in the network, fully distributed adaptive controllers, i.e. requiring no knowledge of the structural eigenvalues nor initial stabilizing control law.Mechanical Engineering | Systems and Contro