Skip to content

Add passivity module, ispassive function, and passivity_test. Introduces optional dependency cvxopt. #739

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
murrayrm merged 21 commits into from
Jun 16, 2022
Merged

Add passivity module, ispassive function, and passivity_test. Introduces optional dependency cvxopt. #739

Changes from 1 commit
Commits
Show all changes
21 commits
Select commit Hold shift + click to select a range
e8e87a4
Add passivity module, is_passive function, and passivity_test.
May 31, 2022
2eef661
Remove dependancies on lmi-sdp and sympy for is_passive.
Jun 6, 2022
147a24e
Use sys.nstates in stead of using A.shape[0]
Jun 6, 2022
fdb2d4a
Attempt to setup cvxopt similar to slycot.
Jun 6, 2022
dc46f3c
Remove unused import.
Mark-Yeatman Jun 7, 2022
0ecc135
Apply suggestions from code review
Mark-Yeatman Jun 7, 2022
649b21e
Update passivity.py
Mark-Yeatman Jun 7, 2022
b73e6fe
Address some review comments.
Jun 13, 2022
cd7ec0f
Update control/passivity.py
Mark-Yeatman Jun 13, 2022
d65f1d2
Remove duplicate "print" statement.
Jun 13, 2022
7e79c82
Fix grammar in doc string.
Jun 13, 2022
c57b928
Another grammar in doc string fix.
Jun 13, 2022
27487a9
Address edge case of stricly proper systems.
Jun 14, 2022
d6916c6
Expand unit tests, add info to doc string for parameters and returns,…
Jun 14, 2022
bb16be0
Parameterize unit tests. Catch edge case of A=0.
Mark-Yeatman Jun 14, 2022
cf0eac3
Run autopep8.
Mark-Yeatman Jun 14, 2022
7e47d80
Add wrapper like functionality for ispassive(), so that it can be cal…
Mark-Yeatman Jun 16, 2022
ce11d0b
mark the whole passivity_test module as skippable
bnavigator Jun 16, 2022
f7d74b2
Fix bug in tests and lti.py.
Jun 16, 2022
0c361df
Merge branch 'main' into passivity-tools
Mark-Yeatman Jun 16, 2022
c2255b0
Fix merge issue.
Jun 16, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Prev Previous commit
Next Next commit
Remove dependancies on lmi-sdp and sympy for is_passive.
  • Loading branch information
Mark
Mark committed Jun 6, 2022
commit 2eef6612a046b2982327a36ffe03beb4a0aa54f3
53 changes: 30 additions & 23 deletions control/passivity.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4,11 +4,8 @@
'''

from . import statesp as ss
Comment thread
bnavigator marked this conversation as resolved.
Outdated
from sympy import symbols, Matrix, symarray
from lmi_sdp import LMI_NSD, to_cvxopt
from cvxopt import solvers

import numpy as np
import cvxopt as cvx
Comment thread
bnavigator marked this conversation as resolved.
Outdated


def is_passive(sys):
Comment thread
Mark-Yeatman marked this conversation as resolved.
Outdated
Expand All @@ -27,28 +24,38 @@ def is_passive(sys):
C = sys.C
D = sys.D

P = Matrix(symarray('p', A.shape))

# enforce symmetry in P
size = A.shape[0]
for i in range(0, size):
for j in range(0, size):
P[i, j] = P[j, i]

# construct matrix for storage function x'*V*x
V = Matrix.vstack(
Matrix.hstack(A.T * P + P*A, P*B - C.T),
Matrix.hstack(B.T*P - C, Matrix(-D - D.T))
def make_LMI_matrix(P):
V = np.vstack((
np.hstack((A.T @ P + P@A, P@B)),
np.hstack((B.T@P, np.zeros_like(D))))
)
return V

P = np.zeros_like(A)
matrix_list = []
state_space_size = A.shape[0]
for i in range(0, state_space_size):
for j in range(0, state_space_size):
if j <= i:
P = P*0.0
Comment thread
bnavigator marked this conversation as resolved.
Outdated
P[i, j] = 1.0
P[j, i] = 1.0
matrix_list.append(make_LMI_matrix(P).flatten())

coefficents = np.vstack(matrix_list).T

constants = -np.vstack((
np.hstack((np.zeros_like(A), - C.T)),
np.hstack((- C, -D - D.T)))
)

# construct LMI, convert to form for feasibility solver
LMI_passivty = LMI_NSD(V, 0*V)
min_obj = 0 * symbols("x")
variables = V.free_symbols
solvers.options['show_progress'] = False
c, Gs, hs = to_cvxopt(min_obj, LMI_passivty, variables)
number_of_opt_vars = int(
(state_space_size**2-state_space_size)/2 + state_space_size)
c = cvx.matrix(0.0, (number_of_opt_vars, 1))

# crunch feasibility solution
sol = solvers.sdp(c, Gs=Gs, hs=hs)
sol = cvx.solvers.sdp(c,
Gs=[cvx.matrix(coefficents)],
hs=[cvx.matrix(constants)])

return (sol["x"] is not None)