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control.optimal.quadratic_cost

control.optimal.quadratic_cost(sys, Q, R, x0=0, u0=0)[source]

Create quadratic cost function.

Returns a quadratic cost function that can be used for an optimal control problem. The cost function is of the form

cost = (x - x0)^T Q (x - x0) + (u - u0)^T R (u - u0)

Parameters:

sysInputOutputSystem: I/O system for which the cost function is being defined.
Q2D array_like: Weighting matrix for state cost. Dimensions must match system state.
R2D array_like: Weighting matrix for input cost. Dimensions must match system input.
x01D array: Nominal value of the system state (for which cost should be zero).
u01D array: Nominal value of the system input (for which cost should be zero).

Returns:

cost_funcallable: Function that can be used to evaluate the cost at a given state and input. The call signature of the function is cost_fun(x, u).

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