Abstract
An approximation-based adaptive design problem for output-constrained tracking of a class of switched pure-feedback nonlinear systems is investigated under arbitrary switchings. All switched nonlinearities are assumed to be unknown. Contrary to the existing control results for uncertain switched pure-feedback nonlinear systems where the number of the used function approximators should be equal to the order of the systems, an adaptive control scheme based on only two neural networks is designed by using a system transformation and the common Lyapunov function method, regardless of the order of the system. In the proposed controller, the output constraints are used to establish designable time-varying bounds on the tracking performance. The stability and the constraint satisfaction of the resulting closed-loop system are shown in the sense of Lyapunov stability criterion. Finally, simulation examples are provided to illustrate the effectiveness of the proposed methodology.
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Recommended by Associate Editor Do Wan Kim under the direction of Editor Euntai Kim. This research was supported by the Chung-Ang University Excellent Student Scholarship in 2016 and by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-H8501-16-1018) supervised by the IITP (Institute for Information & communications Technology Promotion).
Seung-Woo Lee received his B.S. degree from the School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, Korea, in 2015, where he is currently pursuing the Master degree with the Department of Electrical and Electronic Engineering. His current research interests include nonlinear adaptive control, intelligent control using neural networks, and their applications to switched nonlinear systems.
Hyoung-Oh Kim received his B.S. degree from the School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, Korea, in 2016, where he is currently pursuing the Master degree with the Department of Electrical and Electronic Engineering. His current research interests include nonlinear adaptive control, nonlinear disturbance observer, and intelligent control using neural networks.
Sung-Jin Yoo received the B.S., M.S., and Ph.D degrees from Yonsei University, Seoul, Korea, in 2003, 2005, and 2009, respectively, in electrical and electronic engineering. He has been a Post-doctoral researcher in the Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Illinois from 2009 to 2010. He is currently an Associate Professor in the School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, Korea. His research interests include nonlinear adaptive control, decentralized control, distributed control, and neural networks theories, and their applications to robotic, flight, and time-delay systems.
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Lee, S.W., Kim, H.O. & Yoo, S.J. Adaptive neural network tracking of a class of switched nonlinear systems with time-varying output constraints. Int. J. Control Autom. Syst. 15, 1425–1433 (2017). https://doi.org/10.1007/s12555-016-0339-5
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DOI: https://doi.org/10.1007/s12555-016-0339-5