Spacecraft Attitude Measurement and Control Using VSMSCSG and Fractional-Order Zeroing Neural Network Adaptive Steering Law
In order to improve the accuracy and convergence speed of the steering law under the conditions of high dynamics, high bandwidth, and a small deflection angle, and in an effort to improve attitude measurement and control accuracy of the spacecraft, a spacecraft attitude measurement and control metho...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/3/766 |
| _version_ | 1827354537220898816 |
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| author | Lei Li Yuan Ren Weijie Wang Weikun Pang |
| author_facet | Lei Li Yuan Ren Weijie Wang Weikun Pang |
| author_sort | Lei Li |
| collection | DOAJ |
| description | In order to improve the accuracy and convergence speed of the steering law under the conditions of high dynamics, high bandwidth, and a small deflection angle, and in an effort to improve attitude measurement and control accuracy of the spacecraft, a spacecraft attitude measurement and control method based on variable speed magnetically suspended control sensitive gyroscopes (VSMSCSGs) and the fractional-order zeroing neural network (FO-ZNN) steering law is proposed. First, a VSMSCSG configuration is designed to realize attitude measurement and control integration in which the VSMSCSGs are employed as both actuators and attitude-rate sensors. Second, a novel adaptive steering law using FO-ZNN is designed. The matrix pseudoinverses are replaced by FO-ZNN outputs, which solves the problem of accuracy degradation in the traditional pseudoinverse steering laws due to the complexity of matrix pseudoinverse operations under high dynamics conditions. In addition, the convergence and robustness of the FO-ZNN are proven. The results show that the proposed FO-ZNN converges faster than the traditional zeroing neural network under external disturbances. Finally, a new weighting function containing rotor deflection angles is added to the steering law to ensure that the saturation of the rotor deflection angles can be avoided. Semi-physical simulation results demonstrate the correctness and superiority of the proposed method. |
| first_indexed | 2024-03-08T03:50:04Z |
| format | Article |
| id | doaj.art-ab9b197f5fc240918fade826bcf342ec |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-08T03:50:04Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-ab9b197f5fc240918fade826bcf342ec2024-02-09T15:21:47ZengMDPI AGSensors1424-82202024-01-0124376610.3390/s24030766Spacecraft Attitude Measurement and Control Using VSMSCSG and Fractional-Order Zeroing Neural Network Adaptive Steering LawLei Li0Yuan Ren1Weijie Wang2Weikun Pang3Graduate School, Space Engineering University, Beijing 101400, ChinaDepartment of Basic Course, Space Engineering University, Beijing 101400, ChinaDepartment of Astronautical Science and Technology, Space Engineering University, Beijing 101400, ChinaGraduate School, Space Engineering University, Beijing 101400, ChinaIn order to improve the accuracy and convergence speed of the steering law under the conditions of high dynamics, high bandwidth, and a small deflection angle, and in an effort to improve attitude measurement and control accuracy of the spacecraft, a spacecraft attitude measurement and control method based on variable speed magnetically suspended control sensitive gyroscopes (VSMSCSGs) and the fractional-order zeroing neural network (FO-ZNN) steering law is proposed. First, a VSMSCSG configuration is designed to realize attitude measurement and control integration in which the VSMSCSGs are employed as both actuators and attitude-rate sensors. Second, a novel adaptive steering law using FO-ZNN is designed. The matrix pseudoinverses are replaced by FO-ZNN outputs, which solves the problem of accuracy degradation in the traditional pseudoinverse steering laws due to the complexity of matrix pseudoinverse operations under high dynamics conditions. In addition, the convergence and robustness of the FO-ZNN are proven. The results show that the proposed FO-ZNN converges faster than the traditional zeroing neural network under external disturbances. Finally, a new weighting function containing rotor deflection angles is added to the steering law to ensure that the saturation of the rotor deflection angles can be avoided. Semi-physical simulation results demonstrate the correctness and superiority of the proposed method.https://www.mdpi.com/1424-8220/24/3/766variable speed magnetically suspended control sensitive gyroscopefractional-order zeroing neural networksteering lawspacecraft attitude measurement and control integration |
| spellingShingle | Lei Li Yuan Ren Weijie Wang Weikun Pang Spacecraft Attitude Measurement and Control Using VSMSCSG and Fractional-Order Zeroing Neural Network Adaptive Steering Law Sensors variable speed magnetically suspended control sensitive gyroscope fractional-order zeroing neural network steering law spacecraft attitude measurement and control integration |
| title | Spacecraft Attitude Measurement and Control Using VSMSCSG and Fractional-Order Zeroing Neural Network Adaptive Steering Law |
| title_full | Spacecraft Attitude Measurement and Control Using VSMSCSG and Fractional-Order Zeroing Neural Network Adaptive Steering Law |
| title_fullStr | Spacecraft Attitude Measurement and Control Using VSMSCSG and Fractional-Order Zeroing Neural Network Adaptive Steering Law |
| title_full_unstemmed | Spacecraft Attitude Measurement and Control Using VSMSCSG and Fractional-Order Zeroing Neural Network Adaptive Steering Law |
| title_short | Spacecraft Attitude Measurement and Control Using VSMSCSG and Fractional-Order Zeroing Neural Network Adaptive Steering Law |
| title_sort | spacecraft attitude measurement and control using vsmscsg and fractional order zeroing neural network adaptive steering law |
| topic | variable speed magnetically suspended control sensitive gyroscope fractional-order zeroing neural network steering law spacecraft attitude measurement and control integration |
| url | https://www.mdpi.com/1424-8220/24/3/766 |
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