Abstract
This paper proposes an adaptive hierarchical sliding mode control method based on radial basis function neural network for an uncertain 2D overhead crane system. A second-level sliding surface is defined by a linear combination of two subsystem’s sliding surfaces. A radial basis function neural network is adopted to approximate the unknown dynamic model. The control law is designed in order to ensure the stability of sliding surfaces and an updated law for neural network’s weight matrices is derived from a candidate of Lyapunov function. Simulation results show that the effectiveness of the proposed control scheme, such as smaller swing and accurate position as desired. Besides that, the controller is installed in micro-controller for the actual model in laboratory and experiment result evaluate the applicability of this control design in industrial applications.
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Le, H.X., Nguyen, T.V., Le, A.V. et al. Adaptive hierarchical sliding mode control using neural network for uncertain 2D overhead crane. Int. J. Dynam. Control 7, 996–1004 (2019). https://doi.org/10.1007/s40435-019-00524-x
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DOI: https://doi.org/10.1007/s40435-019-00524-x