Adaptive H∞ consensus control of euler-lagrange systems on directed network graph by utilizing neural network approximators

A design method of adaptive consensus control of multi-agent systems composed of fully actuated mobile robots which are described as a class of Euler-Lagrange systems on directed network graphs, is presented in this paper based on the notion of inverse optimal H∞ control criterion. The proposed control scheme is deduced as a solution of certain H∞ control problem, where estimation errors of tuning parameters are considered as external disturbances to the process. The resulting control system is shown to be robust to uncertain system parameters and the approximate consensus tracking is achieved via adaptation schemes and L2-gain design parameters.