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Predictive fault-tolerant control of an all-thruster satellite in 6-DOF motion via neural network model updating

Tavakoli, M. M ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1016/j.asr.2017.12.032
  3. Publisher: Elsevier Ltd , 2018
  4. Abstract:
  5. The problem of controlling an all-thruster spacecraft in the coupled translational-rotational motion in presence of actuators fault and/or failure is investigated in this paper. the nonlinear model predictive control approach is used because of its ability to predict the future behavior of the system. The fault/failure of the thrusters changes the mapping between the commanded forces to the thrusters and actual force/torque generated by the thruster system. Thus, the basic six degree-of-freedom kinetic equations are separated from this mapping and a set of neural networks are trained off-line to learn the kinetic equations. Then, two neural networks are attached to these trained networks in order to learn the thruster commands to force/torque mappings on-line. Different off-nominal conditions are modeled so that neural networks can detect any failure and fault, including scale factor and misalignment of thrusters. A simple model of the spacecraft relative motion is used in MPC to decrease the computational burden. However, a precise model by the means of orbit propagation including different types of perturbation is utilized to evaluate the usefulness of the proposed approach in actual conditions. The numerical simulation shows that this method can successfully control the all-thruster spacecraft with ON-OFF thrusters in different combinations of thruster fault and/or failure. © 2017 COSPAR
  6. Keywords:
  7. 6-DOF satellite control ; All-thruster satellite ; Fault-tolerant control ; Model Predictive Control (MPC) ; Neural network model update ; Degrees of freedom (mechanics) ; Fault tolerance ; Integral equations ; Joints (structural components) ; Kinetic energy ; Kinetic theory ; Mapping ; Numerical methods ; Orbits ; Predictive control systems ; Satellites ; Computational burden ; Fault tolerant control ; Kinetic equations ; Neural network model ; Nonlinear model predictive control ; Satellite control ; Six degree-of-freedom ; Translational-rotational motion ; Model predictive control
  8. Source: Advances in Space Research ; Volume 61, Issue 6 , March , 2018 , Pages 1588-1599 ; 02731177 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/pii/S0273117717309201