Neural networks-based adaptive fault-tolerant control for a class of nonstrict-feedback nonlinear systems with actuator faults and input delay
Open accessAbstract
This paper addresses the challenge of adaptive control for nonstrict-feedback nonlinear systems that involve input delay, actuator faults, and external disturbance. To deal with the complexities arising from input delay and unknown functions, we have incorporated Pade approximation and radial basis function neural networks, respectively. An adaptive controller has been developed by utilizing the Lyapunov stability theorem and the backstepping approach. The suggested method guarantees that the tracking error converges to a compact neighborhood that contains the origin and that every signal in the closed-loop system is semi-globally uniformly ultimately bounded. To demonstrate the efficacy of the proposed method, an electromechanical system application example, and a numerical example are provided. Additionally, comparative analysis was conducted between the Pade approximation proposed in this paper and the auxiliary systems in the existing method. Furthermore, error assessment criteria have been employed to substantiate the effectiveness of the proposed method by comparing it with existing results.
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This paper incorporates unknown backlash-like hysteresis alongside input delay in nonlinear systems, emphasizing fixed-time stability.
“In contrast, this paper incorporates unknown backlash-like hysteresis alongside input delay in nonlinear systems, emphasizing fixed-time stability.”
From Fixed-Time Adaptive Control for Nonstrict-Feedback Nonlinear Systems with Input Delay and Unknown Backlash-Like Hysteresis (2025) · cites this paper as [50]
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Cites
Neural Networks-Based Adaptive Control for Nonlinear State Constrained Systems With Input Delay
Li, D.-P., Liu, Y.-J., Tong, S., Chen, C. L. P., & Li, D.-J. (2019) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2799683 · Cited by 382 · see citing works
Fuzzy Adaptive Finite-Time Fault-Tolerant Control for Strict-Feedback Nonlinear Systems
Sun, K., Liu, L., Qiu, J., & Feng, G. (2020) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2020.2965890 · Cited by 360 · see citing works
Adaptive Fault-Tolerant Control of Uncertain Nonlinear Large-Scale Systems With Unknown Dead Zone
Chen, M., & Tao, G. (2015) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2015.2456028 · Cited by 355 · see citing works
Adaptive Fuzzy Finite-Time Control of Nonlinear Systems With Actuator Faults
Wang, H., Liu, P. X., Zhao, X., & Liu, X. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2019.2902868 · Cited by 345 · see citing works
Sun, K., Qiu, J., Karimi, H. R., & Fu, Y. (2020) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2020.2979129 · Cited by 334 · see citing works
Adaptive Fuzzy Control of Strict-Feedback Nonlinear Time-Delay Systems With Unmodeled Dynamics
Yin, S., Shi, P. J., & Yang, H. (2015) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2015.2457894 · Cited by 305 · see citing works
Liu, Y., Liu, X., & Jing, Y. (2018) · Information Sciences · doi:10.1016/j.ins.2018.08.029 · Cited by 276 · see citing works
Nonsingular Fixed-Time Fault-Tolerant Fuzzy Control for Switched Uncertain Nonlinear Systems
Cui, D., & Xiang, Z. (2022) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2022.3184048 · Cited by 193 · see citing works
Niu, B., & Li, L. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2017.2690465 · Cited by 185 · see citing works
Adaptive Neural Control of Nonlinear Systems With Unknown Control Directions and Input Dead-Zone
Wang, H., Karimi, H. R., Liu, P. X., & Yang, H. (2017) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2017.2709813 · Cited by 184 · see citing works
Wang, T., Ju, W., Wang, Y., & Ma, M. (2019) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2019.2952832 · Cited by 170 · see citing works
Wang, Z., Liu, L., & Zhang, H. (2017) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2017.2672664 · Cited by 163 · see citing works
Adaptive neural control for non-strict-feedback nonlinear systems with input delay
Wang, H., Liu, S., & Yang, X. (2020) · Information Sciences · doi:10.1016/j.ins.2019.09.043 · Cited by 152 · cited 8× · see citing works
“The results, as depicted in Table 2, demonstrate a marginal improvement in the proposed control scheme relative to the existing control method [29].”
MethodResultInfluentialAdaptive fault-tolerant control for switched nonlinear systems based on command filter technique
Wang, Y. Q., Xu, N., Liu, Y., & Zhao, X. (2020) · Applied Mathematics and Computation · doi:10.1016/j.amc.2020.125725 · Cited by 146 · see citing works
Li, Z., Li, T., Feng, G., Zhao, R., & Shan, Q. (2018) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2018.2872421 · Cited by 137 · see citing works
Yang, D., Li, T., Xie, X., & Zhang, H. (2019) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2019.2944404 · Cited by 131 · see citing works
Novel Adaptive Fuzzy Control for Output Constrained Stochastic Nonstrict Feedback Nonlinear Systems
Sun, W., Su, S., Wu, Y., & Xia, J. (2020) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2020.2969909 · Cited by 125 · see citing works
Backstepping adaptive fuzzy control of uncertain nonlinear systems against actuator faults
Li, P., & Yang, G. (2009) · Journal of Control Theory and Applications · doi:10.1007/s11768-009-8074-6 · Cited by 114 · see citing works
Wu, Y., & Xie, X. (2019) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2019.2920808 · Cited by 114 · see citing works
Adaptive finite-time control of stochastic nonlinear systems with actuator failures
Wang, F., Liu, Z., Zhang, Y., & Chen, C. L. P. (2018) · Fuzzy Sets and Systems · doi:10.1016/j.fss.2018.12.005 · Cited by 89 · see citing works
Ma, L., & Liu, L. (2021) · IEEE Transactions on Systems, Man, and Cybernetics: Systems · doi:10.1109/tsmc.2019.2922393 · Cited by 79 · see citing works
Application of Artificial Neural Networks for Multi-Criteria Yield Prediction of Winter Rapeseed
Niedbała, G. (2019) · Sustainability · doi:10.3390/su11020533 · Cited by 55 · see citing works
Disturbance-observer-based adaptive command filtered control for uncertain nonlinear systems
Yang, X., Deng, W., & Yao, J. (2022) · ISA Transactions · doi:10.1016/j.isatra.2022.04.007 · Cited by 52 · see citing works
Dastres, H., Rezaie, B., & Baigzadehnoe, B. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.02.070 · Cited by 51 · see citing works
Su, X., Liu, Z., Lai, G., Zhang, Y., & Chen, C. L. P. (2019) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2019.2898156 · Cited by 46 · see citing works
Yang, Z., Zhang, X., Zong, X., & Wang, G. (2020) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2020.05.008 · Cited by 44 · see citing works
Zhang, J., Xia, J., Sun, W., Wang, Z., & Shen, H. (2019) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2019.05.042 · Cited by 39 · see citing works
Han, Y. (2021) · Nonlinear Dynamics · doi:10.1007/s11071-021-06843-z · Cited by 36 · see citing works
Cui, D., Zou, W., Guo, J. C., & Xiang, Z. (2022) · Applied Mathematics and Computation · doi:10.1016/j.amc.2022.127216 · Cited by 35 · see citing works
Wu, L., & Yang, G. (2015) · Nonlinear Dynamics · doi:10.1007/s11071-015-2235-6 · Cited by 26 · see citing works
Adaptive neural control of non-strict feedback system with actuator failures and time-varying delays
Zhang, Y., & Wang, F. (2019) · Applied Mathematics and Computation · doi:10.1016/j.amc.2019.06.026 · Cited by 25 · see citing works
Cui, D., Zou, W., Guo, J. C., & Xiang, Z. (2022) · International Journal of Adaptive Control and Signal Processing · doi:10.1002/acs.3491 · Cited by 17 · see citing works
Kharrat, M., Krichen, M., Alkhalifa, L., & Gasmi, K. (2023) · AIMS Mathematics · doi:10.3934/math.2024048 · Cited by 15 · see citing works
Self-citationGuo, B., Dian, S., & Zhao, T. (2022) · Nonlinear Dynamics · doi:10.1007/s11071-022-07771-2 · Cited by 14 · see citing works
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Self-citationBouazza, A., Debbi, H., & Lakhlef, H. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-34867-8_2
- Authors
- Kharrat, M., & Alhazmi, H.
- Affiliations
- Jouf University (SA)
- Princess Nourah bint Abdulrahman University (SA)
- Corresponding author
- Alhazmi, Hadil
- Venue
- AIMS Mathematics
- Published
- 2024
- Volume
- 9
- Issue
- 6
- Pages
- 13689-13711
- ISSN
- 2473-6988 (ISSN-L)
- OpenAlex
- W4394827267
- Cited by
- 11
- References
- 34
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 2
- FWCI
- 1.72
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc-sa
- Locations
- AIMS Mathematics (publishedVersion, cc-by-nc-sa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Princess Nourah Bint Abdulrahman University (PNURSP2024R528)
- 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 › Computer Science › Computer Networks and Communications › Neural Networks Stability and Synchronization
- Keywords
- adaptive fault-tolerant control, nonstrict-feedback nonlinear systems, actuator faults, input delay, Padé approximants, radial basis function neural network, backstepping control, semi-global uniform ultimate boundedness, external disturbances, electromechanical systems
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