Fault Detection for Satellite Formation Flight Using Improved Elman Neural Network

Wang, Jiayi; Chen, Hua; Chen, Jia; Bei, Wan; Yang, Shengqing

doi:10.1007/978-981-15-8155-7_105

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Artificial Neural Network (Ann) Model-based Fdi Technique1

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2023

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“…Then, the difference between estimated and actual torque values used to generate threshold and residual for FDI task. [11][12][13][14][15][16].…”

Section: Artificial Neural Network (Ann) Model-based Fdi Techniquementioning

confidence: 99%

Spacecraft fault detection and identification techniques using artificial intelligence

Abdel Aziz,

Salama,

Mohamed

et al. 2023

J. Phys.: Conf. Ser.

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The complexity of spacecraft systems and their missions is increasing, requiring higher levels of performance and innovative solutions. It is essential to have onboard autonomy with minimal faults to ensure reliability, availability, and safety. Fault Detection and Identification (FDI) is critical in identifying spacecraft faults before they cause major failures. However, FDI design and application are challenging due to the space environment and the reliance on system information. To improve accuracy, speed, and noise robustness, modern FDI methods based on Artificial Intelligence (AI) techniques have been developed. This paper investigates the latest FDI techniques in the spacecraft attitude determination and control subsystem (ADCS) and electrical power subsystem (EPS). The article discusses various FDI methodologies and frameworks, highlighting their advantages, drawbacks, and the significance of AI implementation. Additionally, the paper presents a thorough analysis and comparison of the different methods.

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“…Then, the difference between estimated and actual torque values used to generate threshold and residual for FDI task. [11][12][13][14][15][16].…”

Section: Artificial Neural Network (Ann) Model-based Fdi Techniquementioning

confidence: 99%

Spacecraft fault detection and identification techniques using artificial intelligence

Abdel Aziz,

Salama,

Mohamed

et al. 2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

Fault Detection for Satellite Formation Flight Using Improved Elman Neural Network

Cited by 1 publication

References 11 publications

Spacecraft fault detection and identification techniques using artificial intelligence

Spacecraft fault detection and identification techniques using artificial intelligence

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