Cited by 130Adaptive Control of Nonlinear SystemsStability and Control of Uncertain SystemsNeural Networks Stability and Synchronization

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Adaptive Neural Control of MIMO Nonstrict-Feedback Nonlinear Systems With Time Delay

Zhao, Xudong, Yang, Haijiao, Karimi, Hamid Reza, Zhu, Yanzheng·2016·IEEE Transactions on Cybernetics

DOI 10.1109/tcyb.2015.2441292

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Abstract

In this paper, an adaptive neural output-feedback tracking controller is designed for a class of multiple-input and multiple-output nonstrict-feedback nonlinear systems with time delay. The system coefficient and uncertain functions of our considered systems are both unknown. By employing neural networks to approximate the unknown function entries, and constructing a new input-driven filter, a backstepping design method of tracking controller is developed for the systems under consideration. The proposed controller can guarantee that all the signals in the closed-loop systems are ultimately bounded, and the time-varying target signal can be tracked within a small error as well. The main contributions of this paper lie in that the systems under consideration are more general, and an effective design procedure of output-feedback controller is developed for the considered systems, which is more applicable in practice. Simulation results demonstrate the efficiency of the proposed algorithm.

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Self-citation
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“In the work of Zhao et al, 30 an adaptive neural output-feedback tracking controller is developed for a class of MIMO nonstrict-feedback nonlinear systems with time delay and unknown function entries are approximated by employing neural networks.”
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BackgroundMethodInfluential
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Event-Triggered Synchronization Control of Uncertain Neutral-Type Neural Networks With Time-Varying Delays and Actuator Saturation
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“Aswe all know, the network bandwidth is limited [25], [26], therefore, in order to avoid unnecessary waste of resources and reduce network load capacity, the event-triggered mechanism [27] was proposed as a powerful tool and has become a subject of intense research activities [28], [29], [30],…”
Background

Authors: Zhao, X., Yang, H., Karimi, H. R., & Zhu, Y.
Affiliations: Bohai University (CN)
University of Agder (NO)
Harbin Institute of Technology (CN)
ORCID: Zhao, Xudong
Yang, Haijiao
Karimi, Hamid Reza
Zhu, Yanzheng
Venue: IEEE Transactions on Cybernetics
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Published: 2016-06
Volume: 46
Issue: 6
Pages: 1337-1349
ISSN: 2168-2267 (ISSN-L)
2168-2275
DOI: 10.1109/tcyb.2015.2441292
OpenAlex: W2353924536
Cited by: 130
References: 44
Citations by year: 2025: 2 · 2024: 2 · 2023: 2 · 2022: 8 · 2021: 15 · 2020: 11 · 2019: 23 · 2018: 30 · 2017: 30 · 2016: 7
FWCI: 20.68
Type: journal article
Language: en
Open access: closed
Licence: ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations: IEEE Transactions on Cybernetics (publishedVersion)
PubMed (publishedVersion)
Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (submittedVersion)
Funders: National Natural Science Foundation of China (61203123, 61333012)
Liaoning Excellent Talents in University (LR2014035)
Shandong Provincial Natural Science Foundation, China (ZR2012FQ019)
Topics: Physical Sciences › Engineering › Control and Systems Engineering › Adaptive Control of Nonlinear Systems
Physical Sciences › Engineering › Control and Systems Engineering › Stability and Control of Uncertain Systems
Physical Sciences › Engineering › Control and Systems Engineering › Neural Networks Stability and Synchronization
Keywords: adaptive neural network control, MIMO nonlinear systems, nonstrict-feedback systems, time delay, output feedback tracking control, backstepping design, neural network approximation, ultimate boundedness

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Adaptive Neural Control of MIMO Nonstrict-Feedback Nonlinear Systems With Time Delay

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