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Robust neuro‐adaptive cooperative control of multi‐agent port‐controlled Hamiltonian systems

Sami El Ferik, Aminuddin Qureshi, Frank L. Lewis

Year
2015
Citations
9

Abstract

Summary This paper presents the distributed cooperative tracking control of the multi‐agent port‐controlled Hamiltonian (PCH) systems that are networked through a directed graph. Controller is made robust against the parametric uncertainties using neural networks. Dynamics of the the proposed novel neural network tuning law is driven by both the position and the velocity errors owing to the information preserving filtering of the Hamiltonian gradient. In addition, the PCH structure of the closed‐loop system is preserved and the controller achieves the disturbance attenuation objective. Simulations are performed on a group of robotic manipulators to demonstrate the efficacy of the proposed controller. Copyright © 2015 John Wiley & Sons, Ltd.

Keywords

Control theory (sociology)Computer scienceParametric statisticsArtificial neural networkAttenuationHamiltonian (control theory)Hamiltonian systemControl engineeringEngineeringControl (management)

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