Fractional data-driven model for stabilization of uncertain discrete-time nonlinear systems |
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| Institution: | 1. Department of Multidisciplinary Engineering, Texas A&M University, 6200 Tres Lagos Blvd, Higher Education Center at McAllen, McAllen, 78504, Texas, USA;2. Department of Robotics and Advanced Manufacturing, Center for Research and Advanced Studies (CINVESTAV-IPN), Av. Industria Metalurgica, Ramos Arizpe, 25900, Coahuila, Mexico;1. Key Laboratory of Networks and Cloud Computing Security of Universities in Chongqing, School of Electronic and Information Engineering, Southwest University, Chongqing, China;2. School of Cyberspace Security, Beijing Institute of Technology, Beijing, China;1. Research Center of Satellite Technology, Harbin Institute of Technology, Harbin, China;2. Department of Electronic and Information Engineering, College of Engineering, Shantou University, Shantou, China;1. Department of Electrical Engineering, Faculty of Engineering, University of Guilan, Rasht, Iran;2. Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, Trondheim, Norway |
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| Abstract: | This paper proposes a novel data-driven control for stabilization of a class of uncertain discrete-time nonlinear systems. The proposed method is based on the compact form dynamic linearization technique, which relates the first variation of the output signal with the fractional-order variation of the input one. Then, a discrete-time controller is proposed, based on the obtained fractional-order data-driven equivalent model. In order to compute the proposed controller and estimator, only input-output data information is considered. The uniform ultimately boundedness of the tracking errors are demonstrated by a formal analysis. Finally, comparison results based on simulations are presented to highlight the effectiveness of the proposed methodology. |
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