Title: Varying-sliding condition adaptive controller for a class of unknown discrete-time systems with data-driven model

Authors: Chidentree Treesatayapun

Addresses: Department of Robotic and Advanced Manufacturing, CINVESTAV-Saltillo, Ramos Arizpe, 25903, Mexico

Abstract: In this paper, an adaptive controller is developed based on discrete-time sliding mode control with a varying-sliding condition. The controlled plant is considered as an unknown system dynamic. The dynamic model is estimated by a data-driven scheme with pseudo-partial derivative (PPD) of plant's input-output. The convergence analysis of estimated model is established under reasonable assumptions which exist in practical systems. Furthermore, the accuracy of the estimated PPD is verified by the computer simulation system. The control law is designed by the data-driven model and time varying-sliding gain which is proposed to guarantee the convergence of tracking error. A prototype DC-motor current control demonstrates the validation of the proposed control scheme as experimental results. The comparative results with the conventional data-driven controller represent the effectiveness and the applicability of the proposed controller.

Keywords: discrete-time systems; adaptive control; data-driven model; sliding mode control; dc-motor control.

DOI: 10.1504/IJMIC.2017.083784

International Journal of Modelling, Identification and Control, 2017 Vol.27 No.3, pp.210 - 218

Available online: 22 Apr 2017 *

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