Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural Networks
This study investigates the design of fault-tolerant control involving adaptive nonsingular fast terminal sliding mode control and neural networks. Unlike those of previous control strategies, the adaptive law of the investigated algorithm is considered in both continuous and discontinuous terms, wh...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/8/9/1541 |
| _version_ | 1797554215232471040 |
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| author | Ngoc Phi Nguyen Nguyen Xuan Mung Le Nhu Ngoc Thanh Ha Tuan Tu Huynh Sung Kyung Hong |
| author_facet | Ngoc Phi Nguyen Nguyen Xuan Mung Le Nhu Ngoc Thanh Ha Tuan Tu Huynh Sung Kyung Hong |
| author_sort | Ngoc Phi Nguyen |
| collection | DOAJ |
| description | This study investigates the design of fault-tolerant control involving adaptive nonsingular fast terminal sliding mode control and neural networks. Unlike those of previous control strategies, the adaptive law of the investigated algorithm is considered in both continuous and discontinuous terms, which means that any disturbances, model uncertainties, and actuator faults can be simultaneously compensated for. First, a quadcopter model is presented under the conditions of disturbances and uncertainties. Second, normal adaptive nonsingular fast terminal sliding mode control is utilized to handle these disturbances. Thereafter, fault-tolerant control based on adaptive nonsingular fast terminal sliding mode control and neural network approximation is presented, which can handle the actuator faults, model uncertainties, and disturbances. For each controller design, the Lyapunov function is applied to validate the robustness of the investigated method. Finally, the effectiveness of the investigated control approach is presented via comparative numerical examples under different fault conditions and uncertainties. |
| first_indexed | 2024-03-10T16:27:33Z |
| format | Article |
| id | doaj.art-8a7331d73e83495aa4341597ebff0a4b |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T16:27:33Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-8a7331d73e83495aa4341597ebff0a4b2023-11-20T13:04:11ZengMDPI AGMathematics2227-73902020-09-0189154110.3390/math8091541Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural NetworksNgoc Phi Nguyen0Nguyen Xuan Mung1Le Nhu Ngoc Thanh Ha2Tuan Tu Huynh3Sung Kyung Hong4Department of Aerospace Engineering, Sejong University, Seoul 143-747 (05006), KoreaDepartment of Aerospace Engineering, Sejong University, Seoul 143-747 (05006), KoreaSchool of Intelligent Mechatronics Engineering, Sejong University, Seoul 143-747 (05006), KoreaDepartment of Electrical Engineering, Yuan Ze University, No. 135, Yuandong Road, Zhongli, Taoyuan 320, TaiwanDepartment of Aerospace Engineering, Sejong University, Seoul 143-747 (05006), KoreaThis study investigates the design of fault-tolerant control involving adaptive nonsingular fast terminal sliding mode control and neural networks. Unlike those of previous control strategies, the adaptive law of the investigated algorithm is considered in both continuous and discontinuous terms, which means that any disturbances, model uncertainties, and actuator faults can be simultaneously compensated for. First, a quadcopter model is presented under the conditions of disturbances and uncertainties. Second, normal adaptive nonsingular fast terminal sliding mode control is utilized to handle these disturbances. Thereafter, fault-tolerant control based on adaptive nonsingular fast terminal sliding mode control and neural network approximation is presented, which can handle the actuator faults, model uncertainties, and disturbances. For each controller design, the Lyapunov function is applied to validate the robustness of the investigated method. Finally, the effectiveness of the investigated control approach is presented via comparative numerical examples under different fault conditions and uncertainties.https://www.mdpi.com/2227-7390/8/9/1541sliding mode controlfault tolerant controlquadcopter unmanned aerial vehicles (UAVs)neural network |
| spellingShingle | Ngoc Phi Nguyen Nguyen Xuan Mung Le Nhu Ngoc Thanh Ha Tuan Tu Huynh Sung Kyung Hong Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural Networks Mathematics sliding mode control fault tolerant control quadcopter unmanned aerial vehicles (UAVs) neural network |
| title | Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural Networks |
| title_full | Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural Networks |
| title_fullStr | Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural Networks |
| title_full_unstemmed | Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural Networks |
| title_short | Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural Networks |
| title_sort | finite time attitude fault tolerant control of quadcopter system via neural networks |
| topic | sliding mode control fault tolerant control quadcopter unmanned aerial vehicles (UAVs) neural network |
| url | https://www.mdpi.com/2227-7390/8/9/1541 |
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