Yoshihiko Miyasato
adaptive control , multi-agent system, consensus control, H-infinity control, nonlinear control, network graph
In this paper, we present design principles of asymptotically stable adaptive H-infinity consensus control of multi-agent systems composed of the first and second order regression models on directed network graphs. The essential point is that we deduce the proposed control schemes as solutions of a class of H-infinity control problem, where estimation errors of tuning parameters are regarded as external disturbances in the H-infinity control setting. It is shown that the resulting control systems are robust to uncertain variations of system parameters, and that the desirable consensus tracking is achieved asymptotically via adaptation schemes and L2-gain design parameters together with an introduction of the generating model of the leader, which promotes asymptotic consensus tracking.
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