Nonparametric output prediction for nonlinear fading memory systems

@article{Kulkarni1999NonparametricOP,
  title={Nonparametric output prediction for nonlinear fading memory systems},
  author={Sanjeev R. Kulkarni and S. E. Posner},
  journal={IEEE Trans. Autom. Control.},
  year={1999},
  volume={44},
  pages={29-37}
}
The authors construct a class of elementary nonparametric output predictors of an unknown discrete-time nonlinear fading memory system. Their algorithms predict asymptotically well for every bounded input sequence, every disturbance sequence in certain classes, and every linear or nonlinear system that is continuous and asymptotically time-invariant, causal, and with fading memory. The predictor is based on k/sub n/-nearest neighbor estimators from nonparametric statistics. It uses only… 
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8 Citations

Universal output prediction and nonparametric regression for arbitrary data

We construct a class of elementary nonparametric output predictors of an unknown discrete-time nonlinear fading memory system. Our algorithms predict asymptotically well for every bounded input…

Nonparametric control algorithms for nonlinear fading memory systems

  • S. SandilyaS. Kulkarni
  • Computer Science, Mathematics
    Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304)
  • 1999
An algorithm is developed to control an unknown nonlinear fading memory discrete-time system based on nonparametric regression techniques rather than traditional feedback control and produces an output that converges to the desired output when stricter conditions are imposed on the system.

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