control.optimal.gaussian_likelihood_cost
- control.optimal.gaussian_likelihood_cost(sys, Rv, Rw=None)[source]
Create cost function for Gaussian likelihoods.
Returns a quadratic cost function that can be used for an optimal estimation problem. The cost function is of the form
cost = v^T R_v^{-1} v + w^T R_w^{-1} w
- Parameters
- sys
InputOutputSystem I/O system for which the cost function is being defined.
- Rv2D array_like
Covariance matrix for input (or state) disturbances.
- Rw2D array_like
Covariance matrix for sensor noise.
- sys
- Returns
- cost_funcallable
Function that can be used to evaluate the cost for a given disturbance and sensor noise. The call signature of the function is cost_fun(v, w).