Adaptive H∞ consensus control of euler-lagrange systems on directed network graph by utilizing neural network approximators | IEEE Conference Publication | IEEE Xplore

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


Abstract:

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 ...Show More

Abstract:

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 and with nonlinear terms approximated by neural networks, is presented in this paper. The proposed control scheme is derived as a solution of certain H control problem, where estimation errors of tuning parameters and approximate and algorithmic errors in neural network estimation schemes are regarded as external disturbances to the process, and the controllers are to be designed in order to attenuate the effects of those disturbances based on H criterion. The resulting control system is shown to be robust to uncertain system parameters and nonlinear elements, and the approximate consensus tracking is achieved via adaptation schemes and L2-gain design parameters.
Date of Conference: 27 November 2017 - 01 December 2017
Date Added to IEEE Xplore: 05 February 2018
ISBN Information:
Conference Location: Honolulu, HI, USA

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