Indirect sliding mode neural-network control for holonomic constrained robot manipulators Online publication date: Sat, 31-Jul-2010
by Emna Zouari, Hanene Medhaffar, Nabil Derbel
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 9, No. 2, 2010
Abstract: This paper presents an adaptive neural network (NN) sliding mode control (NNSMC) for the motion and force control of constrained robot manipulators. Radial basis function (RBF) NNs are used as estimators to approximate the uncertainties in the problem formulation. Adaptive learning algorithms in NNSMC are derived from the Lyapunov stability analysis, so that the stability of the proposed control scheme is proved. Simulations are performed to demonstrate the effectiveness of the proposed controller.
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