LQP
Class method.
- LQP(A, B, nx, nu, system_type='discrete', sampling_rate=1.0, t0=0.0, method='euler')
Initialize the system with linear dynamics.
In this case the right hand side of the dynamics has the form :
\[f(x,u) = Ax+Bu\]which is always
autonomous. If not a fixed step method is choosen for integration the optimizer can not use the linear structure of the problem during the optimization process.- Parameters:
A (array) – Matrix definig the linear state input on the right hand side of the dynamics.
B (array) – Matrix definig the linear state input on the right hand side of the dynamics.
nx (int) – Dimension of the state. Must be a positive integer. See also
nx.nu (int) – Dimension of the control. Must be a positive integer. See also
nu.system_type (str, optional) – String defining whether the given system dynamics are discrete or continuous. The default is ‘discrete’.
sampling_rate (float, optional) – Sampling rate defining at which time instances the dynamics are evaluated. The default is 1.
t0 (float, optional) – Initial time for the optimal control problem. The default is 0. See also
t0.method (str, optional) – String defining which integration method should be used to discretize the system dynamics. The default is ‘euler’. For further informations about the provided integrators see
method.
- Returns:
lqp – nMPyC-system class object suitable to define a linear quadratic optimal control problem..
- Return type: