runge-kutta-4 | The fourth order Runge-Kutta integration method | SMS library
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The fourth order Runge-Kutta integration method
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QUESTION
I am trying to implement the classical RK4 algorithm to solve the system of differential equations which govern the equations of motion. However, I am having several problems for a while. The equations of motion can be written as below:
Since this is a system of first order differential equations, we are ready to use RK4 to solve it. However, I am really lost in regards to writing the system above in python code.
There is a related question here: System of second order ODEs Runge Kutta 4th order which writes the system of ODES for a different physical system into Python code and also uses RK4 to solve it. However, I have not been able to use that to make my own code work. There is another question I want to have the pendulum blob in my double pendulum which is closer to what I want, but it does not take care of the process by using arrays, but rather by writing several equations instead.
...ANSWER
Answered 2021-Jul-12 at 00:04You are not using the passed state variable in the derivatives function, you just set the state to a constant. You should have a line like
QUESTION
I'm implementing the Runge-Kutta-4 method for ODE approximation with a step correction procedure. Here's the code:
...ANSWER
Answered 2021-May-01 at 11:45v2 = v2 + RK4(v+v2,h/2,cant_ec)
is wrong, it should be v2 = RK4(v2,h/2,cant_ec)
, as the result of RK4
is the next point, not the update to the next point. As the error calculation is thus wrong, the step size gets reduced indefinitely. After some 50 reductions, the RK4 step will no longer advance the state, the increment being too small.
It will lead to problems if you have a fixed step number with a variable step size.
The inner loop does not make any sense whatsoever. The overall effect is that after each step size reduction i
gets incremented by one. So theoretically, if n<50
the program should terminate, but with a final state very close to the initial state.
The local error should be compared to tol*h
, so that the global error becomes proportional to tol
.
There should also be an instruction that increases h
if the local error becomes too small.
See How to perform adaptive step size using Runge-Kutta fourth order (Matlab)? for another example of using RK4 with step-size control by double steps.
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