NDLI: Real-time adaptive control of robot manipulator based on neural network compensator

Content Provider	IEEE Xplore Digital Library
Author	Huu Cong-Nguyen Woo-Song Lee Dong-Han Lee Sung-Hyun Han
Copyright Year	2008
Description	Author affiliation: Div. of Mech. Syst. & Autom. Eng., Kyungnam Univ., Masan (Dong-Han Lee; Sung-Hyun Han) \|\| Grad. Sch., Kyungnam Univ., Masan (Huu Cong-Nguyen; Woo-Song Lee)
Abstract	This paper presents two kinds of adaptive control schemes for robot manipulator which has the parametric uncertainties. In order to compensate these uncertainties, we use the NN (neural network system) that has the capability to approximate any nonlinear function over the compact input space. In the proposed control schemes, we need not derive the linear formulation of robot dynamic equation and tune the parameters. We also suggest the robust adaptive control laws in all proposed schemes for decreasing the effect of approximation error. To reduce the number of neural of network, we consider the properties of robot dynamics and the decomposition of the uncertainty function. The proposed controllers are robust not only to the structured uncertainty such as payload parameter, but also to the unstructured one such as friction model and disturbance. The validity of the control scheme is shown by computer simulations and experiment of dual-arm robot manipulator.
Starting Page	2590
Ending Page	2595
File Size	1460849
Page Count	6
File Format	PDF
ISBN	9788995003893
DOI	10.1109/ICCAS.2008.4694293
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-14
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	ICROS
Subject Keyword	Uncertainty Nonlinear equations decomposition Nonlinear dynamical systems uncertainty Adaptive control Adaptive tracking control neural network systems Orbital robotics Robust control robot dynamics Neural networks Approximation error Robots Manipulator dynamics
Content Type	Text
Resource Type	Article

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