System Identification using the Neural-Extended Kalman Filter for Control Modification

  title={System Identification using the Neural-Extended Kalman Filter for Control Modification},
  author={Stephen C. Stubberud},
  journal={The 2006 IEEE International Joint Conference on Neural Network Proceedings},
The neural extended Kalman filter has been shown to be able to work and train on-line in a control loop and as a state estimator for maneuver target tracking. Often, however, the design of a control system does not have a state estimator in the feedback loop. The ability of the NEKF to learn dynamics in an open-loop implementation, such as with target tracking and intercept prediction, can be used to identify mis-modeled dynamics. The improved system model can then be used to adapt the control… CONTINUE READING
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