Thanks to visit codestin.com
Credit goes to github.com

Skip to content

Minimal example: use GN Hessian, improve warning #1135

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
merged 2 commits into from
Jun 14, 2024
Merged

Minimal example: use GN Hessian, improve warning #1135

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
51d3c0d
change minimal example to NONLINEAR_LS cost formulation for real GN H…
FreyJo Jun 14, 2024
8632c5b
improve warning to not exclude CONL
FreyJo Jun 14, 2024
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
20 changes: 13 additions & 7 deletions examples/acados_python/getting_started/minimal_example_ocp.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,7 @@
from acados_template import AcadosOcp, AcadosOcpSolver
from pendulum_model import export_pendulum_ode_model
import numpy as np
import casadi as ca
from utils import plot_pendulum

def main():
Expand All @@ -52,16 +53,21 @@ def main():
# set prediction horizon
ocp.solver_options.tf = Tf

# set cost
# cost matrices
Q_mat = 2*np.diag([1e3, 1e3, 1e-2, 1e-2])
R_mat = 2*np.diag([1e-2])

# the 'EXTERNAL' cost type can be used to define general cost terms
# NOTE: This leads to additional (exact) hessian contributions when using GAUSS_NEWTON hessian.
ocp.cost.cost_type = 'EXTERNAL'
ocp.cost.cost_type_e = 'EXTERNAL'
ocp.model.cost_expr_ext_cost = model.x.T @ Q_mat @ model.x + model.u.T @ R_mat @ model.u
ocp.model.cost_expr_ext_cost_e = model.x.T @ Q_mat @ model.x
# path cost
ocp.cost.cost_type = 'NONLINEAR_LS'
ocp.model.cost_y_expr = ca.vertcat(model.x, model.u)
ocp.cost.yref = np.zeros((nx+nu,))
ocp.cost.W = ca.diagcat(Q_mat, R_mat).full()

# terminal cost
ocp.cost.cost_type_e = 'NONLINEAR_LS'
ocp.cost.yref_e = np.zeros((nx,))
ocp.model.cost_y_expr_e = model.x
ocp.cost.W_e = Q_mat

# set constraints
Fmax = 80
Expand Down
2 changes: 1 addition & 1 deletion interfaces/acados_template/acados_template/acados_ocp.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -201,7 +201,7 @@ def make_consistent(self) -> None:
if opts.hessian_approx == 'GAUSS_NEWTON' and opts.ext_cost_num_hess == 0 and model.cost_expr_ext_cost_custom_hess_0 is None:
print("\nWARNING: Gauss-Newton Hessian approximation with EXTERNAL cost type not possible!\n"
"got cost_type_0: EXTERNAL, hessian_approx: 'GAUSS_NEWTON.'\n"
"GAUSS_NEWTON hessian is only supported for cost_types [NON]LINEAR_LS.\n"
"GAUSS_NEWTON hessian is not defined for EXTERNAL cost formulation.\n"
"If you continue, acados will proceed computing the exact hessian for the cost term.\n"
"Note: There is also the option to use the external cost module with a numerical hessian approximation (see `ext_cost_num_hess`).\n"
"OR the option to provide a symbolic custom hessian approximation (see `cost_expr_ext_cost_custom_hess`).\n")
Expand Down