Adaptive finite‐time stabilizing control of fractional‐order nonlinear systems with unmodeled dynamics via sampled‐data output‐feedback

Author:

Mao Jun1,Wang Ronghao2,Zou Wencheng3,Xiang Zhengrong3ORCID

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

Abstract

AbstractThis 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.

Publisher

Wiley

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