Reputation: 37
I want to solve a non linear ordinary differential equation of the form
Theta2 = (C + j(Theta2))**-1 * (f(t) – g(Theta1) -h(Theta0))
Where f(), g(), h(), and j() are functions already defined that take Theta2, Theta1, Theta0 or t as an input. Theta2 and Theta1 are the second and first derivative of Theta0 with time t.
I have been solving the equation without the j(Theta2) term using the SciPy.odeint function using the following code:
from scipy.integrate import odeint
def ODE():
def g(Theta, t):
Theta0 = Theta[0]
Theta1 = Theta[1]
Theta2 = (1/C)*( f(t) - g(Theta1) - h(Theta0))
return Theta1, Theta2
init = 0, 0 # Initial conditions on theta0 and theta1 (velocity) at t=0
sol=odeint(g, init, t)
A = sol[:,1]
B = sol[:,0]
return(A, B)
Upvotes: 0
Views: 1749
Reputation: 4151
The equation could be re-written as:
F(t, theta, theta')
theta'' = -------------------
a + b*theta''
where a and b are constants, and F corresponds to (f(t) – g(Theta1) -h(Theta0)).
It is a second order polynomial function of theta'', with 2 solutions (considering b!=0 and a^2 + 4*b*F>0) :
theta'' = -( sqrt(a^2 + 4*b*F) +/- a )/(2*b)
This new equation is of the form y' = f(t, y) which could be solved using regular ODE solver.
Here is an example using solve_ivp which is the replacement for odeint:
import numpy as np
from scipy.integrate import solve_ivp
import matplotlib.pyplot as plt
a = 20
b = 1
def f(t, y, dydt):
return t + y**2
def ode_function_plus(t, Y):
y = Y[0]
dydt = Y[1]
d2y_dt2 = -(np.sqrt(a**2 + 4*b*f(t, y, dydt)) + a )/(2*b)
return [dydt, d2y_dt2]
def ode_function_minus(t, Y):
y = Y[0]
dydt = Y[1]
d2y_dt2 = -(np.sqrt(a**2 + 4*b*f(t, y, dydt)) - a )/(2*b)
return [dydt, d2y_dt2]
# Solve
t_span = [0, 4]
Y0 = [10, 1]
sol_plus = solve_ivp(ode_function_plus, t_span, Y0)
sol_minus = solve_ivp(ode_function_minus, t_span, Y0)
print(sol_plus.message)
# Graph
plt.plot(sol_plus.t, sol_plus.y[0, :], label='solution +a');
plt.plot(sol_minus.t, sol_minus.y[0, :], label='solution -a');
plt.xlabel('time'); plt.ylabel('y'); plt.legend();
Upvotes: 1