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

@article{Stubberud2006SystemIU,
  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},
  year={2006},
  pages={4449-4455}
}
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
2 Citations
4 References
Similar Papers

Citations

Publications citing this paper.

References

Publications referenced by this paper.
Showing 1-4 of 4 references

An Adaptive Extended Kalman Filter Using Artificial Neural Networks

  • S. Stubberud, M. Owen
  • The International Journal on Smart System Design
  • 1998

Controller Modification Using Improved Models Of The Neural Extended Kalman Filter Training multilayer perceptrons with the extended Kalman algorithm , ”

  • D. S. Touretsky
  • Advances in Neural Processing Systems I ,

Similar Papers

Loading similar papers…