Neural-Networks-Based Adaptive Fault-Tolerant Control of Nonlinear Systems With Actuator Faults and Input Quantization
In this work, the neural networks-based adaptive fault-tolerant control problem for nonlinear systems with actuator faults and input quantization is investigated. To approximate the nonlinear functions in the control system, radial basis function neural networks (RBFNN) are introduced. Additionally,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10336788/ |
| _version_ | 1827398968462540800 |
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| author | Mohamed Kharrat Moez Krichen Loay Alkhalifa Karim Gasmi |
| author_facet | Mohamed Kharrat Moez Krichen Loay Alkhalifa Karim Gasmi |
| author_sort | Mohamed Kharrat |
| collection | DOAJ |
| description | In this work, the neural networks-based adaptive fault-tolerant control problem for nonlinear systems with actuator faults and input quantization is investigated. To approximate the nonlinear functions in the control system, radial basis function neural networks (RBFNN) are introduced. Additionally, an adaptive fault-tolerant controller is presented for nonlinear systems to compensate for the effects of input quantization and actuator fault using the backstepping approach and Lyapunov stability theory. It is demonstrated that with the proposed control strategy, all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to an arbitrarily small area of origin. The simulation results of an electromechanical system are shown to verify the validity of the control approach. |
| first_indexed | 2024-03-08T19:36:32Z |
| format | Article |
| id | doaj.art-9aeb6c62ad73449bb9654a8d8a8ca826 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-08T19:36:32Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-9aeb6c62ad73449bb9654a8d8a8ca8262023-12-26T00:09:02ZengIEEEIEEE Access2169-35362023-01-011113768013768710.1109/ACCESS.2023.333837610336788Neural-Networks-Based Adaptive Fault-Tolerant Control of Nonlinear Systems With Actuator Faults and Input QuantizationMohamed Kharrat0https://orcid.org/0009-0007-0867-9598Moez Krichen1https://orcid.org/0000-0001-8873-9755Loay Alkhalifa2Karim Gasmi3https://orcid.org/0000-0003-0138-2226Department of Mathematics, College of Science, Jouf University, Sakaka, Saudi ArabiaFaculty of Computer Science and Information Technology (CSIT), Al-Baha University, Alaqiq, Saudi ArabiaDepartment of Mathematics, College of Sciences and Arts, Qassim University, Ar Rass, Saudi ArabiaDepartment of Computer Science, College of Arts and Sciences at Tabarjal, Jouf University, Sakakah, Saudi ArabiaIn this work, the neural networks-based adaptive fault-tolerant control problem for nonlinear systems with actuator faults and input quantization is investigated. To approximate the nonlinear functions in the control system, radial basis function neural networks (RBFNN) are introduced. Additionally, an adaptive fault-tolerant controller is presented for nonlinear systems to compensate for the effects of input quantization and actuator fault using the backstepping approach and Lyapunov stability theory. It is demonstrated that with the proposed control strategy, all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to an arbitrarily small area of origin. The simulation results of an electromechanical system are shown to verify the validity of the control approach.https://ieeexplore.ieee.org/document/10336788/Adaptive controlnonlinear systemsLyapunov functionactuator faultsquantizationelectromechanical system |
| spellingShingle | Mohamed Kharrat Moez Krichen Loay Alkhalifa Karim Gasmi Neural-Networks-Based Adaptive Fault-Tolerant Control of Nonlinear Systems With Actuator Faults and Input Quantization IEEE Access Adaptive control nonlinear systems Lyapunov function actuator faults quantization electromechanical system |
| title | Neural-Networks-Based Adaptive Fault-Tolerant Control of Nonlinear Systems With Actuator Faults and Input Quantization |
| title_full | Neural-Networks-Based Adaptive Fault-Tolerant Control of Nonlinear Systems With Actuator Faults and Input Quantization |
| title_fullStr | Neural-Networks-Based Adaptive Fault-Tolerant Control of Nonlinear Systems With Actuator Faults and Input Quantization |
| title_full_unstemmed | Neural-Networks-Based Adaptive Fault-Tolerant Control of Nonlinear Systems With Actuator Faults and Input Quantization |
| title_short | Neural-Networks-Based Adaptive Fault-Tolerant Control of Nonlinear Systems With Actuator Faults and Input Quantization |
| title_sort | neural networks based adaptive fault tolerant control of nonlinear systems with actuator faults and input quantization |
| topic | Adaptive control nonlinear systems Lyapunov function actuator faults quantization electromechanical system |
| url | https://ieeexplore.ieee.org/document/10336788/ |
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