Neural network-based event-triggered data-driven control of disturbed nonlinear systems with quantized input

Wang, Xianming; Karimi, Hamid Reza; Shen, Mouquan; Liu, Dan; Li, Li-Wei; Shi, Jiantao

doi:10.1016/j.neunet.2022.09.021

Cited by 31Stability and Control of Uncertain SystemsAdaptive Control of Nonlinear SystemsNeural Networks Stability and Synchronization

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Neural network-based event-triggered data-driven control of disturbed nonlinear systems with quantized input

Wang, Xianming, Karimi, Hamid Reza, Shen, Mouquan, Liu, Dan, Li, Li-Wei, Shi, Jiantao·2022·Neural Networks

DOI 10.1016/j.neunet.2022.09.021

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Abstract

This paper is devoted to design an event-triggered data-driven control for a class of disturbed nonlinear systems with quantized input. A uniform quantizer reconstructed with decreasing quantization intervals is employed to reduce the quantization error. A neural network-based estimation strategy is proposed to estimate both the pseudo partial derivative and disturbances. Consequently, an input triggering rule for single-input single-output systems is provided by incorporating the estimated disturbances, the quantization error bound and tracking errors. Resorting to the Lyapunov method, sufficient conditions for synthesized error systems to be uniformly ultimately bounded are presented. The validity of the proposed scheme is demonstrated via a simulation example.

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Authors: Wang, X., Karimi, H. R., Shen, M., Liu, D., Li, L.-W., & Shi, J.
Affiliations: Nanjing Tech University (CN)
Politecnico di Milano (IT)
Corresponding author: Karimi, Hamid Reza
Shen, Mouquan
ORCID: Wang, Xianming
Karimi, Hamid Reza
Shen, Mouquan
Liu, Dan
Shi, Jiantao
Venue: Neural Networks
Publisher: Elsevier BV
Published: 2022-12
Volume: 156
Pages: 152-159
ISSN: 0893-6080 (ISSN-L)
DOI: 10.1016/j.neunet.2022.09.021
OpenAlex: W4300981574
Cited by: 31
References: 24
Citations by year: 2026: 3 · 2025: 5 · 2024: 13 · 2023: 10
FWCI: 2.82
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
doi.org/10.15223/policy-017 (stm-asf)
doi.org/10.15223/policy-037 (stm-asf)
doi.org/10.15223/policy-012 (stm-asf)
doi.org/10.15223/policy-029 (stm-asf)
doi.org/10.15223/policy-004 (stm-asf)
Locations: Neural Networks (publishedVersion)
PubMed (publishedVersion)
Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (submittedVersion)
Funders: Ministero dell’Istruzione, dell’Università e della Ricerca
National Natural Science Foundation of China (62103185, 61773200, 62173177, 61973288)
Topics: Physical Sciences › Engineering › Control and Systems Engineering › Stability and Control of Uncertain Systems
Physical Sciences › Engineering › Control and Systems Engineering › Adaptive Control of Nonlinear Systems
Physical Sciences › Engineering › Control and Systems Engineering › Neural Networks Stability and Synchronization
Keywords: event-triggered control, data-driven control, nonlinear systems, quantized input, uniform quantizer, quantization error, disturbance estimation, neural network estimation, uniform ultimate boundedness, Lyapunov stability
MeSH terms: Computer Simulation, Neural Networks, Computer, Nonlinear Dynamics

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Neural network-based event-triggered data-driven control of disturbed nonlinear systems with quantized input

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