Mathematics |
Solving ODE Problems
This section uses the van der Pol equation
to describe the process for solving initial value ODE problems using the ODE solvers.
Note See ODE Solver Basic Syntax for more information. |
Example: Solving an IVP ODE (van der Pol Equation, Nonstiff)
This example explains and illustrates the steps you need to solve an initial value ODE problem.
t
and y
must be the function's first two arguments, the function does not need to use them. The output dydt
, a column vector, is the derivative of y
.
The code below represents the van der Pol system in the function, vdp1
. The vdp1
function assumes that . and become elements y(1)
and y(2)
of a two-element vector.
Note that, although vdp1
must accept the arguments t
and y
, it does not use t
in its computations.
ode45
on time interval [0 20]
with initial values y(1) = 2
and y(2) = 0
.
This example uses @
to pass vdp1
as a function handle to ode45
. The resulting output is a column vector of time points t
and a solution array y
. Each row in y
corresponds to a time returned in the corresponding row of t
. The first column of y
corresponds to , and the second column to .
Note
See the function_handle (@), func2str , and str2func reference pages, and the Function Handles chapter of "Programming and Data Types" in the MATLAB documentation for information about function handles.
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plot
command to view the solver output.
OutputFcn
after each successful time step. Use odeset
to set OutputFcn
to the desired function. See OutputFcn for more information.
Passing Additional Parameters to an ODE Function
The solver passes any input parameters that follow the options
argument to the ODE function and any function you specify in options
. For example:
mu
parameter, instead of specifying a value for mu
explicitly in the code.
mu
to the function vdp1
by specifying it after the options
argument in the call to the solver. This example uses options = []
as a placeholder.
See the vdpode
code for a complete example based on these functions.
Example: The van der Pol Equation, µ = 1000 (Stiff)
This example presents a stiff problem. For a stiff problem, solutions can change on a time scale that is very short compared to the interval of integration, but the solution of interest changes on a much longer time scale. Methods not designed for stiff problems are ineffective on intervals where the solution changes slowly because they use time steps small enough to resolve the fastest possible change.
When is increased to 1000, the solution to the van der Pol equation changes dramatically and exhibits oscillation on a much longer time scale. Approximating the solution of the initial value problem becomes a more difficult task. Because this particular problem is stiff, a solver intended for nonstiff problems, such as ode45
, is too inefficient to be practical. A solver such as ode15s
is intended for such stiff problems.
The vdp1000
function evaluates the van der Pol system from the previous example, but with = 1000.
Note
This example hardcodes in the ODE function. The vdpode example solves the same problem, but passes a user-specified as an additional argument to the ODE function. See Additional ODE Solver Arguments.
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Now use the ode15s
function to solve the problem with the initial condition vector of [2; 0]
, but a time interval of [0 3000]
. For scaling purposes, plot just the first component of y(t)
.
[t,y] = ode15s(@vdp1000,[0 3000],[2; 0]); plot(t,y(:,1),'-'); title('Solution of van der Pol Equation, \mu = 1000'); xlabel('time t'); ylabel('solution y_1');
Note For detailed instructions for solving an initial value ODE problem, see Example: Solving an IVP ODE (van der Pol Equation, Nonstiff). |
Evaluating the Solution at Specific Points
The numerical methods implemented in the ODE solvers produce a continuous solution over the interval of integration . You can evaluate the approximate solution, , at any point in using the function deval
and the structure sol
returned by the solver.
The ODE solvers return the structure sol
when called with a single output argument.
The deval
function is vectorized. For a vector xint
, the i
th column of Sxint
approximates the solution .
Initial Value Problem Solvers | Changing ODE Integration Properties |