Neural networks-based adaptive fault-tolerant control for stochastic nonlinear systems with unknown backlash-like hysteresis and actuator faults
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Neural networks have been successfully used to address a wide range of control problems involving unknown system dynamics.
“Additionally, leveraging the universal function approximation property of neural networks, researchers have successfully addressed a wide range of control problems involving unknown system dynamics [16,17].”
From Predefined-Time Tracking Control of Servo Hydraulic Cylinder Based on Reinforcement Learning (2025) · cites this paper as [17]
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Gaufan, K. S. B., Aremu, M. B., Alyazidi, N. M., & Nasir, A. (2025) · Franklin Open · doi:10.1016/j.fraope.2025.100287 · Cited by 21 · see citing works
Kharrat, M. (2024) · Communications in Nonlinear Science and Numerical Simulation · doi:10.1016/j.cnsns.2024.108478 · Cited by 19 · see citing works
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“Therefore, there is no need to use the backstepping technique in the controller design process, making the design simpler compared with the studies Kharrat (2024), Y.H. Ma et al. (2024) and Yu et al. (2020).”
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“These factors make it difficult for conventional control methods to maintain accuracy and robustness, especially under real-world operating conditions [4], [5].”
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“Similarly,forstochasticnonlinearsystemswithunknownbacklash-likehysteresis,an adaptivefault-tolerantcontrolmethodhasbeenreported[23].”
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“In addition, we validate the efcacy of our proposed method by evaluating the error criteria as defned in [8], contrasting it with an existing approach [25].”
Self-citationKharrat, M., & Mercorelli, P. (2025) · Mathematics · doi:10.3390/math14010030 · Cited by 4 · see citing works
Self-citationKharrat, M., & Mercorelli, P. (2026) · Mathematics · doi:10.3390/math14081256 · Cited by 4 · see citing works
“This review aims to explore their individual roles, comparative effectiveness, integration into adaptive control frameworks (such as backstepping), and application to various nonlinear system categories including those with uncertainties, faults, and practical nonlinearities [15–19].”
Self-citationKharrat, M., & Mercorelli, P. (2025) · Mathematics · doi:10.3390/math14010014 · Cited by 3 · see citing works
Self-citationAlhazmi, H., & Kharrat, M. (2024) · AIMS Mathematics · doi:10.3934/math.20241008 · Cited by 3 · see citing works
Self-citationKharrat, M. (2025) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.70235 · Cited by 2 · see citing works
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“Additionally, leveraging the universal function approximation property of neural networks, researchers have successfully addressed a wide range of control problems involving unknown system dynamics [16,17].”
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“Faults that impact system performance can be cate-gorised based on their occurrence location into actuator faults, sensor faults, and component faults (Kharrat, 2024a; Kharrat et al., 2023).”
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“The authors in [20, 21] designed adaptive controllers based on neural networks under hysteresis for large-scale nonlinear systems and non-strict feedback stochastic nonlinear systems, respectively, and proved that all signals of the closed-loop system are semi-globally ultimately uniformly bounded.”
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“42 By adding non-integer order derivatives to the sliding surface or control law, FOSMC, an extension of SMC, improves smoothness and robustness trade-offs, increases tuning freedom, and better manages complex manipulator dynamics.”
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Self-citation
- Authors
- Kharrat, M.
- Affiliations
- Jouf University (SA)
- Corresponding author
- Kharrat, Mohamed
- ORCID
- Kharrat, Mohamed
- Venue
- Journal of Applied Mathematics and Computing
- Published
- 2024-03-20
- Volume
- 70
- Issue
- 3
- Pages
- 1995-2018
- ISSN
- 1226-0061 (ISSN-L)
- 1598-5865
- 1865-2085
- OpenAlex
- W4392990535
- Cited by
- 37
- References
- 45
- Citations by year
- 2026: 18 · 2025: 17 · 2024: 2
- FWCI
- 5.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Journal of Applied Mathematics and Computing (publishedVersion)
- 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 › Fault Detection and Control Systems
- Keywords
- adaptive fault-tolerant control, nonlinear stochastic systems, backlash-like hysteresis, actuator faults, nonstrict-feedback systems, radial basis function neural network, backstepping control, semi-global uniform ultimate boundedness, single-link manipulator
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