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A New Adaptive Neuro-sliding Mode Control for Gantry Crane

Slim Frikha*, Mohamed Djemel, and Nabil Derbel
International Journal of Control, Automation, and Systems, vol. 16, no. 2, pp.559-565, 2018

Abstract : "This paper presents a new adaptive neuro-sliding mode control for gantry crane as varying rope length. This control method derived from combining the sliding surfaces of three subsystem of the gantry crane (trolley position, rope length, anti-swing) to draw out two system sliding surfaces: the trolley position with the anti-swing and the rope length and the anti-swing. On the based of the sliding mode control principle, drawn out the equivalent controller and the switching controller for gantry crane. But due to the uncertain parameters-nonlinear model of gantry crane with the bound disturbances, combining the neural approximate method, defined the neural controller and the compensation controller for the difference between the equivalent controller and the neural controller for two system control inputs: trolley position and rope length. The adaptive control laws for these controllers were deduced from Lyapunov’s stable criteria to asymptotically stabilize the sliding surfaces. Simulation studies are performed to illustrate the effectiveness of the proposed control."

Keyword : Adaptive controller, artificial neural networks, gantry crane, sliding mode control, stability.

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