A sampled-data control problem of neural-network-based systems using an improved free-matrix-based inequality |
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Authors: | SH Lee MJ Park OM Kwon R Sakthivel |
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Institution: | 1. School of Electrical Engineering, Chungbuk National University, 1 Chungdae-ro, Cheongju 28644, Republic of Korea;2. Center for Global Converging Humanities, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin 17104, Republic of Korea;3. Department of Applied Mathematics, Bharathiar University, Coimbatore 641046, India |
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Abstract: | In this work, a sampled-data control problem for neural-network-based systems with an optimal guaranteed cost is investigated. By constructing suitable time-dependent functionals and utilizing an improved free-matrix-based integral inequality, a sampled-data stability criterion for neural-network-based systems is derived. Based on a first result, a sampled-data controller design method for neural-network-based systems that meets the maximum sampling period and minimum guaranteed cost performance is proposed. The superiority and validity of the results will be verified by comparing with the existing results in a numerical example. |
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Keywords: | Corresponding authors |
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