Abstract
In this paper, a novel intelligent digital redesign (IDR) method for a Takagi-Sugeno fuzzy system is proposed based on the guaranteed cost method. The objective of the IDR is to determine a sample-data data gain that achieves the same performance as a given continuous-time controller. Unlike previous works, we use the state-matching error cost function and develop an IDR technique without the use of any discretization methods. To this end, a sufficient condition guaranteeing both the asymptotic stabilization of the error dynamics model and the minimization of the upper bound of the error cost function is formulated in terms of linear matrix inequalities based on the input-delay approach. Finally, a simulation example validates the superiority of the proposed method.
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Recommended by Associate Editor Ho Jae Lee under the direction of Editor Euntai Kim. This work was supported by Barun ICT Research Center at Yonsei University, and by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2016R1A6A1A03013567) and by the Ministry of Trade, Industry & Energy (MOTOE) of the Republic of Korea (No. 20174030201670).
Han Sol Kim received his B.S. degree in Electronic and Computer Engineering from Hanyang University, Korea, in 2011 and his M.S. degree in Electrical and Electronic Engineering, Yonsei University, Korea, in 2012. From 2012, he is working toward a Ph.D. degree in Electrical and Electronic Engineering, Yonsei University, Korea. His current research interests include sampled-data control of fuzzy systems, fuzzy-model-based control, and interconnected fuzzy systems.
Jin Bae Park received his B.S. degree in Electrical Engineering from Yonsei University, Korea, and his M.S. and Ph.D. degrees in Electrical Engineering from Kansas State University, Manhattan, KS, USA, in 1977, 1985, and 1990, respectively. Since 1992, he has been with the School of Electrical and Electronic Engineering, Yonsei University, where he is currently a Professor. His major research interests include robust control and filtering, nonlinear control, intelligent mobile robot, drone, fuzzy control, neural networks, adaptive dynamic programming, chaos theory, and genetic algorithms. Dr. Park served as the Editor-in-Chief for the International Journal of Control, Automation, and Systems (20062010) and the President for the Institute of Control, Robot, and Systems Engineers (2013). He served as the Senior Vice-President for Yonsei University (2014-2015).
Young Hoon Joo received his B.S., M.S., and Ph.D. degrees in Electrical Engineering from Yonsei University, Korea, in 1982, 1984, and 1995, respectively. He worked with Samsung Electronics Company, Korea, from 1986 to 1995, as a Project Manager. He was with the University of Houston, Houston, TX, USA, from 1998 to 1999, as a Visiting Professor with the Department of Electrical and Computer Engineering. He is currently a Professor with the Department of Control and Robotics Engineering, Kunsan National University, Korea. His major research interests include the field of intelligent robot, robot vision, intelligent control, humanrobot interaction, wind-farm control, and intelligent surveillance systems. Dr. Joo served as the President for the Korea Institute of Intelligent Systems (2008-2009), the Vice-President for the Korean Institute of Electrical Engineers (2013-2014), and the Editor-in-Chief for the International Journal of Control, Automation, and Systems (2014-2017).
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Kim, H.S., Park, J.B. & Joo, Y.H. Sampled-data Control of Fuzzy Systems Based on the Intelligent Digital Redesign Technique: An Input-delay Approach. Int. J. Control Autom. Syst. 16, 327–334 (2018). https://doi.org/10.1007/s12555-017-0268-y
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DOI: https://doi.org/10.1007/s12555-017-0268-y