Observer-based synergetic adaptive neural network control for a class of discrete-time nonlinear systems with dead-zone
Shiyi Zhao,
Hongjing Liang and
Peihao Du
International Journal of Systems Science, 2019, vol. 50, issue 9, 1826-1834
Abstract:
In this paper, the observer-based synergetic adaptive neural network control method is designed for a class of discrete-time systems with dead-zone. A macro-variable is introduced by a synergetic approach to control theory and neural networks are utilised to estimate unmeasured states and unknown functions in the system. Furthermore, by employing an adaptive design procedure and Lyapunov stability theory, the closed-loop system stability is guaranteed, and the desired system performance is achieved simultaneously. Finally, some simulation results are given to prove the validity of the developed control method.
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:50:y:2019:i:9:p:1826-1834
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DOI: 10.1080/00207721.2019.1645230
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