- class sympy.physics.mechanics.linearize.Linearizer(f_0, f_1, f_2, f_3, f_4, f_c, f_v, f_a, q, u, q_i=None, q_d=None, u_i=None, u_d=None, r=None, lams=None)[source]#
This object holds the general model form for a dynamic system. This model is used for computing the linearized form of the system, while properly dealing with constraints leading to dependent coordinates and speeds.
f_0, f_1, f_2, f_3, f_4, f_c, f_v, f_a
(Matrix) Matrices holding the general system form.
q, u, r
(Matrix) Matrices holding the generalized coordinates, speeds, and input vectors.
(Matrix) Matrices of the independent generalized coordinates and speeds.
(Matrix) Matrices of the dependent generalized coordinates and speeds.
(Matrix) Permutation matrix such that [q_ind, u_ind]^T = perm_mat*[q, u]^T
- linearize(op_point=None, A_and_B=False, simplify=False)[source]#
Linearize the system about the operating point. Note that q_op, u_op, qd_op, ud_op must satisfy the equations of motion. These may be either symbolic or numeric.
op_point : dict or iterable of dicts, optional
Dictionary or iterable of dictionaries containing the operating point conditions. These will be substituted in to the linearized system before the linearization is complete. Leave blank if you want a completely symbolic form. Note that any reduction in symbols (whether substituted for numbers or expressions with a common parameter) will result in faster runtime.
A_and_B : bool, optional
If A_and_B=False (default), (M, A, B) is returned for forming [M]*[q, u]^T = [A]*[q_ind, u_ind]^T + [B]r. If A_and_B=True, (A, B) is returned for forming dx = [A]x + [B]r, where x = [q_ind, u_ind]^T.
simplify : bool, optional
Determines if returned values are simplified before return. For large expressions this may be time consuming. Default is False.
Note that the process of solving with A_and_B=True is computationally intensive if there are many symbolic parameters. For this reason, it may be more desirable to use the default A_and_B=False, returning M, A, and B. More values may then be substituted in to these matrices later on. The state space form can then be found as A = P.T*M.LUsolve(A), B = P.T*M.LUsolve(B), where P = Linearizer.perm_mat.