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ESANN
2004

A sliding mode controller using neural networks for robot manipulator

9 years 3 months ago
A sliding mode controller using neural networks for robot manipulator
Abstract. This paper proposes a new sliding mode controller using neural networks. Multilayer neural networks with the error back-propagation learning algorithm are used to compensate for the system uncertainty in order to reduce tracking errors and control torques. The stability of the proposed control scheme is proved with the Lyapunov function method. Computer simulation shows that the proposed neuro-controller yields better control performance than the conventional sliding mode controller in the view of tracking errors and overall control torque.
Hajoon Lee, Dongkyung Nam, Cheol Hoon Park
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2004
Where ESANN
Authors Hajoon Lee, Dongkyung Nam, Cheol Hoon Park
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