1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158
|
#
# This file is part of CasADi.
#
# CasADi -- A symbolic framework for dynamic optimization.
# Copyright (C) 2010-2023 Joel Andersson, Joris Gillis, Moritz Diehl,
# KU Leuven. All rights reserved.
# Copyright (C) 2011-2014 Greg Horn
#
# CasADi is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 3 of the License, or (at your option) any later version.
#
# CasADi is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with CasADi; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
#
# IDAS integrator
# =====================
#
# We solve a system
# $\dot{x}(t)=f(x(t),y(t),t)$
# $0=g(x(t),y(t),t)$
from casadi import *
from numpy import *
from pylab import *
# We solve the following simple dae system that describes
# the dynamics of a pendulum:
# x' = u, y' = v, u' = lambda * x, v' =lambda * y - g
# s.t. x^2+y^2 = L
#
# We retain g and L as parameters
# http://en.wikipedia.org/wiki/Differential_algebraic_equation#Examples
L = SX.sym("L")
g = SX.sym("g")
# differential states
x=SX.sym("x")
y=SX.sym("y")
u=SX.sym("u")
v=SX.sym("v")
# algebraic states
lambd=SX.sym("lambda")
# All states and parameters
x_all = vertcat(x,u,y,v)
z_all = lambd
p_all = vertcat(L,g)
# the initial state of the pendulum
P_ = [5,10] # parameters
X_ = [3,-1.0/3,4,1.0/4] # differential states
XDOT_ = [-1.0/3,1147.0/240,1.0/4,-653.0/180] # state derivatives
Z_ = [1147.0/720] # algebraic state
# We construct the DAE system
ode = vertcat(u,lambd*x,v,lambd*y+g)
alg = x**2+y**2-L**2
dae = {'x':x_all, 'z':z_all, 'p':p_all, 'ode':ode, 'alg':alg}
f = Function('f', [x_all, z_all, p_all], [ode, alg], ['x', 'z', 'p'], ['ode', 'alg'])
# Let's check we have consistent initial conditions:
res = f(p=P_, x=X_, z=Z_)
print(res['ode']) # This should be same as XDOT_
print(res['alg']) # This should be all zeros
# Let's check our jacobian $\frac{dg}{dy}$:
j = jacobian(alg,lambd)
print(j)
# Note that the jacobian is not invertible: it is not of DAE-index 1
#
# This system is not solvable with idas, because it is of DAE-index 3.
# It is impossible to lambda from the last element of the residual.
# We create a DAE system solver
I = integrator('I', 'idas', dae, {'calc_ic':False, 'init_xdot':XDOT_})
# This system is not solvable with idas, because it is of DAE-index 3.
# It is impossible obtain lambda from the last element of the residual.
try:
I(p=P_, x0=X_, z0=Z_)
except Exception as e:
print(e)
# We construct a reworked version od the DAE (index reduced), now it is DAE-index 1
ode = vertcat(u,lambd*x)
alg = vertcat(x**2+y**2-L**2, u*x+v*y,u**2-g*y+v**2+L**2*lambd)
x_all = vertcat(x,u)
z_all = vertcat(y,v,lambd)
dae = {'x':x_all, 'z':z_all, 'p':p_all, 'ode':ode, 'alg':alg}
f = Function('f', [x_all, z_all, p_all], [ode, alg], ['x', 'z', 'p'], ['ode', 'alg'])
# the initial state of the pendulum
P_ = [5,10] # parameters
X_ = [3,-1.0/3] # differential states
XDOT_ = [-1.0/3,1147.0/240] # state derivatives
Z_ = [4,1.0/4,1147.0/720] # algebraic state
# Let's check we have consistent initial conditions:
res = f(p=P_, x=X_, z=Z_)
print(res['ode']) # This should be the same as XDOT_
print(res['alg']) # This should be all zeros
# Let's check our jacobian:
J = f.factory('J', f.name_in(), ['jac:alg:z'])
res = J(p=P_, x=X_, z=Z_)
print(array(res["jac_alg_z"]))
# $\frac{dg}{dy}$ is invertible this time.
# We create a DAE system solver
I = integrator('I', 'idas', dae, {'t0':0, 'tf':1, 'init_xdot':XDOT_})
res = I(p=P_, x0=X_, z0=Z_)
print(res['xf'])
# Possible problems
# ==================
# If you would initialize with:
P_ = [5,10] # parameters
X_ = [5,0] # states
# You will get an error:
try:
I(p=P_, x0=X_, z0=Z_)
except Exception as e:
print(e)
# Although this initialisation is consistent,
# it coincides with a singular point.
|