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doc: MHE custom constraint in readme
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README.md

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@@ -109,4 +109,5 @@ for more detailed examples.
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- 🛣️ **Bumpless Transfer**: Smooth transitions from manual to automatic control.
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- ⌚️ **Timing**: Estimators available in filter (current) or predictor (delayed) forms.
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- 🏷️ **MHE Types**: Formulations for both linear (quadratic optimization) and nonlinear plants.
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- 🛡️ **MHE Constraints**: Tunable soft/hard constraints on state and noise estimates.
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- 🚧 **MHE Bounds**: Soft/hard limits on state and noise estimates.
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- 🚫 **MHE Constraints**: Soft/hard custom nonlinear inequality constrains.

src/estimator/mhe/construct.jl

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@@ -252,12 +252,12 @@ N_k = \begin{cases}
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H_e & k ≥ H_e \end{cases}
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```
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The vectors ``\mathbf{Ŵ}`` and ``\mathbf{V̂}`` respectively encompass the estimated process
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noises ``\mathbf{ŵ}(k-j+p)`` from ``j=N_k`` to ``1`` and sensor noises ``\mathbf{v̂}(k-j+1)``
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from ``j=N_k`` to ``1``. The arguments of ``\mathbf{g_c}`` include the extended vectors of
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the estimated states ``\mathbf{X̂_e}``, estimated sensor noises ``\mathbf{V̂_e}``, estimated
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process noises ``\mathbf{Ŵ_e}``, manipulated inputs ``\mathbf{U_e}``, measured outputs
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``\mathbf{Y_e^m}``and measured disturbances ``\mathbf{D_e}``. The Extended Help details all
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these vectors, the slack variable ``ε`` and the estimation of the covariance at arrival
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noises ``\mathbf{ŵ}(k-j+p)`` and sensor noises ``\mathbf{v̂}(k-j+1)`` from ``j=N_k`` to ``1``.
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The arguments of ``\mathbf{g_c}`` include the extended vectors of the estimated states
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``\mathbf{X̂_e}``, estimated sensor noises ``\mathbf{V̂_e}``, estimated process noises
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``\mathbf{Ŵ_e}``, manipulated inputs ``\mathbf{U_e}``, measured outputs ``\mathbf{Y_e^m}``
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and measured disturbances ``\mathbf{D_e}``. The Extended Help details all these vectors, the
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slack variable ``ε`` and the estimation of the covariance at arrival
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``\mathbf{P̂}_{k-N_k}(k-N_k+p)``. If the keyword argument `direct=true` (default value), the
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constant ``p=0`` in the equations above, and the MHE is in the current form. Else ``p=1``,
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leading to the prediction form.

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