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Illustration of how to use nonlinear recursive least square to adapt prediction models online

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AdaptablePrediction

Illustration of how to use nonlinear recursive least square to adapt prediction models online

Require Matlab2019a or above

Run adaptable_prediction.mlx to visualize trajectory prediction results under different circumstances. Tunable parameters:

  1. system parameter
  2. prediction horizon
  3. forgetting factor

Nonlinear prediction model

x(k+1) = f(a(k), x(k))

Noninear recursive least square

[To be completed]

References

https://en.wikipedia.org/wiki/Recursive_least_squares_filter

https://en.wikipedia.org/wiki/Extended_Kalman_filter

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Illustration of how to use nonlinear recursive least square to adapt prediction models online

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