Adaptive finite-time stabilizing control of fractional-order nonlinear systems with unmodeled dynamics via sampled-data output-feedback |
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| Authors: | Jun Mao Ronghao Wang Wencheng Zou Zhengrong Xiang |
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| Affiliation: | 1. Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province, China Jiliang University, Hangzhou, China;2. College of Defense Engineering, Army Engineering University of PLA, Nanjing, China;3. School of Automation, Nanjing University of Science and Technology, Nanjing, China |
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| Abstract: | This article realizes an adaptive finite-time sampled-data output-feedback stabilization for a class of fractional-order nonlinear systems with unmodeled dynamics and unavailable states. K-filters are constructed to estimate unavailable states, a dynamic signal is introduced to handle unmodeled dynamics and neural networks were used to approximate uncertain nonlinearities existed in stabilizer construction. With the help of backstepping technique, an adaptive sampled-data output-feedback stabilizer is exported, and such stabilizer with allowable design parameters and sampling period can render the corresponding closed-loop system reaches practically finite-time stable, which can be demonstrated by means of selected Lyapunov function candidates. In the end, two simulations with a numerical and an engineering examples are presented to verify the effectiveness of the proposed scheme. |
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| Keywords: | finite-time control fractional-order nonlinear systems output-feedback control sampled-data control unmodeled dynamics |
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