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Regular papers

Adaptive output-feedback control for a class of stochastic nonlinear systems with unknown control directions and hysteresis input

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Pages 657-670 | Received 09 Jul 2020, Accepted 10 Oct 2020, Published online: 28 Oct 2020
 

Abstract

This paper is concerned with an adaptive neural output-feedback control for a class of stochastic nonlinear systems with unknown control directions and hysteresis input. An output-feedback controller is developed for stochastic nonlinear via using radial basis function neural networks (RBFNNs) and adaptive backstepping method. A state observer is designed to estimate the unmeasurable system state signals. Nussbaum gain technique is employed to deal with the unknown control directions. Simultaneously, the backlash-like hysteresis input control in this paper is considered. An adaptive controller is designed to ensure that the output tracking error converges on a small region of the origin. Finally, the control scheme ensures that all signals in the closed-loop systems are semi-global uniformly ultimately bounded. Results of simulation cases are presented to prove the effectivity of the theoretical analysis.

Acknowledgments

The author would like to thank the reviewers and associate editor for their valuable suggestions and comments.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes on contributors

Fei Shen was born in Anhui Province, China, on June 5. 1994. He received the B.S. degree in Electronic Information Engineering from West Anhui University, Lu'an, China, in 2017. He is currently working toward the Ph.D. degree with Hohai University, Nanjing, China. His research interest include intelligent control systems, neural networks, nonlinear system and signal processing.

Xinjun Wang was born in Shandong Province, China, on February 1. 1991. He received the M.S. degree in Control Theory and Control Engineering from Bohai University in 2016 and the Ph.D. degree in Information and Communication Engineering from Hohai University in 2020. He is currently working in the College of Information Science and Engineering, Shandong Normal University. His research interests include adaptive control theory and application of nonlinear systems, hybrid systems, multi-agent systems and cyber physical systems.

Xinghui Yin was born in Hunan, China, in 1962. He received the B.S. degree in electromagnetic engineering from Xi'dian University, China, in 1983. Since 1983, he has been with Purple Mountain Observatory, National Astronomical Observatories of China, Chinese Academy of Sciences, Jiangsu, China, where he was engaged in several radio telescopes, remote sensing radiometers, and satellite earth station development projects. His research activities include radio-heliograph, low noise receivers, and remote sensing measurement.

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