کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1715349 1519975 2012 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Intelligent fault-tolerant control for swing-arm system in the space-borne spectrograph
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی هوافضا
پیش نمایش صفحه اول مقاله
Intelligent fault-tolerant control for swing-arm system in the space-borne spectrograph
چکیده انگلیسی

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.


► Two-layer intelligent fault-tolerant control (FTC) is used in the swing-arm system.
► Fault detection is carried out for the anticipated or unanticipated faults and SEUs.
► Radial basis function neural network is used to diagnose the unanticipated faults.
► Reliability of FTC at performance level is enhanced by fault detection at code level.
► An implementation of control flow checking by software signatures in actual system.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Acta Astronautica - Volume 73, April–May 2012, Pages 67–75
نویسندگان
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