Brief paper: Decentralized adaptive controller design of large-scale uncertain robotic systems

Authors:
Kok Kiong Tan;Sunan Huang;Tong Heng Lee
Affiliations:
Department of Electrical Engineering, National University of Singapore, Singapore;Department of Electrical Engineering, National University of Singapore, Singapore;Department of Electrical Engineering, National University of Singapore, Singapore
Venue:
Automatica (Journal of IFAC)
Year:
2009

Citing 8
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Abstract

In this paper, we develop a decentralized neural network control design for robotic systems. Using this design, it is not necessary to derive the robotic dynamical system (robotic model) for the control of each of the robotic components, as in traditional robot control. The advantage of the proposed neural network controller is that, under a mild assumption, unknown nonlinear dynamics such as inertia matrix and Coriolis/centripetal matrix and friction, as well as interconnections with arbitrary nonlinear bounds can be accommodated with on-line learning.