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scipy.signal.ss2tf¶
- scipy.signal.ss2tf(A, B, C, D, input=0)[source]¶
State-space to transfer function.
A, B, C, D defines a linear state-space system with p inputs, q outputs, and n state variables.
Parameters: A : array_like
State (or system) matrix of shape (n, n)
B : array_like
Input matrix of shape (n, p)
C : array_like
Output matrix of shape (q, n)
D : array_like
Feedthrough (or feedforward) matrix of shape (q, p)
input : int, optional
For multiple-input systems, the index of the input to use.
Returns: num : 2-D ndarray
Numerator(s) of the resulting transfer function(s). num has one row for each of the system’s outputs. Each row is a sequence representation of the numerator polynomial.
den : 1-D ndarray
Denominator of the resulting transfer function(s). den is a sequence representation of the denominator polynomial.
Examples
Convert the state-space representation:
˙x(t)=[−2−110]x(t)+[10]u(t)y(t)=[12]x(t)+[1]u(t)>>> A = [[-2, -1], [1, 0]] >>> B = [[1], [0]] # 2-dimensional column vector >>> C = [[1, 2]] # 2-dimensional row vector >>> D = 1
to the transfer function:
H(s)=s2+3s+3s2+2s+1>>> from scipy.signal import ss2tf >>> ss2tf(A, B, C, D) (array([[1, 3, 3]]), array([ 1., 2., 1.]))