On-Board Model Based Fault Diagnosis for CubeSat Attitude Control Subsystem: Flight Data Results

被引:3
|
作者
Mackey, Ryan [1 ]
Nikora, Allen [1 ]
Altenbuchner, Cornelia [1 ]
Bocchino, Robert [1 ]
Sievers, Michael [1 ]
Fesq, Lorraine [1 ]
Kolcio, Ksenia O. [2 ]
Litke, Matthew J. [2 ]
Prather, Maurice [2 ]
机构
[1] CALTECH, Jet Prop Lab, 4800 Oak Grove Dr, Pasadena, CA 91109 USA
[2] Okean Solut Inc, 1211 E Denny Way,32A, Seattle, WA 98112 USA
关键词
D O I
10.1109/AERO50100.2021.9438342
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Self-sufficient, robotic spacecraft require estimates of their hardware health state in order to project future system state and plan actions toward achieving mission goals. In this paper, we report on integration of a Model-Based Fault Diagnosis (MBFD) model and reasoning engine into flight software leveraging the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, including test results against captured flight data using the ASTERIA system testbed. Our effort integrated the Model-based Off-Nominal State Identification and Detection (MONSID) model-based reasoning system, developed by Okean Solutions, into ASTERIA flight software using the F Prime software framework. The MONSID engine was supplied with a model of the Blue Canyon Technologies XACT attitude control system (ACS) and tested against flight data and seeded fault tests. While we were unable to conduct an on-board experiment due to the premature loss of ASTERIA, our effort proved the feasibility of on-board model-based fault management, demonstrating reliable and accurate diagnosis using captured data, and further supporting a closed-loop spacecraft autonomy demonstration including autonomous navigation in off-nominal conditions.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Embedded model-based fault diagnosis for on-board diagnosis of engine control systems
    Weinhold, N
    Ding, SX
    Jeinsch, T
    Schultalbers, M
    2005 IEEE INTERNATIONAL CONFERENCE ON CONTROL APPLICATIONS (CCA), VOLS 1AND 2, 2005, : 1206 - 1211
  • [2] Dynamic neural network-based fault diagnosis for attitude control subsystem of a satellite
    Li, Z. Q.
    Ma, L.
    Khorasani, K.
    PRICAI 2006: TRENDS IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2006, 4099 : 308 - 318
  • [3] Fault Diagnosis for On-board Equipment of Train Control System Based on CNN-CSRF Hybrid Model
    Zhou L.
    Dang J.
    Wang Y.
    Zhang Z.
    Tiedao Xuebao/Journal of the China Railway Society, 2020, 42 (11): : 94 - 101
  • [4] Model-based fault diagnosis for satellite heat control subsystem
    Fan, Xian-Feng
    Jiang, Xing-Wei
    Huang, Wen-Hu
    Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology, 2001, 33 (03): : 318 - 320
  • [5] On-board fault diagnosis of automated manual transmission control system
    Qin, GH
    Ge, AL
    Li, HS
    IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2004, 12 (04) : 564 - 568
  • [6] Data Analysis and Results of the Radiation-Tolerant Collaborative Computer On-Board OPTOS CubeSat
    Martin-Ortega, Alberto
    Rodriguez, Santiago
    de Mingo, Jose R.
    Ibarmia, Sergio
    Rivas, Joaquin
    Lopez-Buedo, Sergio
    Lopez-Ongil, Celia
    Portela-Garcia, Marta
    INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING, 2019, 2019
  • [7] Model predictive and reallocation problem for CubeSat fault recovery and attitude control
    Franchi, Loris
    Feruglio, Lorenzo
    Mozzillo, Raffaele
    Corpino, Sabrina
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2018, 98 : 1034 - 1055
  • [8] Fault diagnosis of an actuator in the attitude control subsystem of a satellite using neural networks
    Li, Z. Q.
    Ma, L.
    Khorasani, K.
    2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6, 2007, : 2657 - 2662
  • [9] On-board fault diagnosis system of automated manual transmission control system
    Qin, GH
    Ge, AL
    Wang, FY
    2003 IEEE INTELLIGENT TRANSPORTATION SYSTEMS PROCEEDINGS, VOLS. 1 & 2, 2003, : 932 - 937
  • [10] Data-Driven Failure Characteristics and Reliability Analysis for Train Control On-Board Subsystem
    Bin Chen
    Cai, Baigen
    Wei Shangguan
    Jian Wang
    IEEE ACCESS, 2019, 7 : 126489 - 126499