Stable adaptive compensation with fuzzy CMAC for an overhead crane |
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Authors: | Wen Yu Marco A. Moreno-Armendariz |
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Affiliation: | a Departamento de Control Automatico, CINVESTAV-IPN, A.P. 14-740, Av., IPN 2508, México D.F., 07360, Mexico b Centro de Investigación en Computación-IPN, AV. Juan de Dios Bátiz S/N, Unidad Profesional “Adolfo López Mateos” México D.F., 07738, Mexico |
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Abstract: | In order to control mechanical systems, this paper proposes a novel fast control strategy. The controller includes a normal proportional and derivative (PD) regulator and a fuzzy cerebellar model articulation controller (CMAC). For an overhead crane, this control can realize both position tracking and anti-swing. Using a Lyapunov method and an input-to-state stability technique, the PD control with CMAC compensation is proven to be robustly stable with bounded uncertainties. Real-time experiments are presented comparing this new stable control strategy with regular crane controllers. |
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Keywords: | Cerebellar model articulation controller Neural compensation Stability Overhead crane |
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