Article ID: | iaor20121691 |
Volume: | 73 |
Issue: | 2 |
Start Page Number: | 67 |
End Page Number: | 75 |
Publication Date: | Apr 2012 |
Journal: | Acta Astronautica |
Authors: | Shi Yufeng, Zhou Chunjie, Huang Xiongfeng, Yin Quan |
Keywords: | space, neural networks, design |
Fault‐tolerant control (FTC) for the space‐borne equipments is very important in the engineering design. This paper presents a two‐layer intelligent FTC approach to handle the speed stability problem in the swing‐arm system suffering from various faults in space. This approach provides the reliable FTC at the performance level, and improves the control flow error detection capability at the code level. The faults degrading the system performance are detected by the performance‐based fault detection mechanism. The detected faults are categorized as the anticipated faults and unanticipated faults by the fault bank. Neural network is used as an on‐line estimator to approximate the unanticipated faults. The compensation control and intelligent integral sliding mode control are employed to accommodate two types of faults at the performance level, respectively. To guarantee the reliability of the FTC at the code level, the key parts of the program codes are modified by control flow checking by software signatures (CFCSS) to detect the control flow errors caused by the single event upset. Meanwhile, some of the undetected control flow errors can be detected by the FTC at the performance level. The FTC for the anticipated fault and unanticipated fault are verified in Synopsys Saber, and the detection of control flow error is tested in the DSP controller. Simulation results demonstrate the efficiency of the novel FTC approach.