The Computable Differential Equation Lecture ... - Bruce E. Shapiro
The Computable Differential Equation Lecture ... - Bruce E. Shapiro
The Computable Differential Equation Lecture ... - Bruce E. Shapiro
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CHAPTER 7. DELAY DIFFERENTIAL EQUATIONS 147<br />
ListPlot[results, PlotJoined -> True, PlotLabel -> ‘‘tau’’ <br />
ToString[tau], Frame->True, AspectRatio-> 0.3]<br />
Figure 7.3 illustrates the results when this DDE is solved using τ = 1, 4, 7, 15, 20,<br />
showing a constant steady state, damped oscillations, stable regular oscillations,<br />
irregular oscillations, and chaotic oscillations. <strong>The</strong> point to be gained from this is<br />
that even with constant initial conditions (g(t) = 1) the behavior of the solution<br />
can change radically with different size delays.<br />
7.4 Runge-Kutta Methods for Delay <strong>Differential</strong> <strong>Equation</strong>s<br />
Delay differential equations can be solved using Runge-Kutta methods. Suppose<br />
that we have an equation with a single delay that we wish toslve,<br />
It is convenient to use a fixed step size such that<br />
y ′ (t) = f(t, y(t), y(t − τ)) (7.73)<br />
y(t) = g(t), t 0 − τ < t < t 0 (7.74)<br />
τ = kh (7.75)<br />
for some integer k. <strong>The</strong>n the corresponding Runge-Kutta method is<br />
K (n)<br />
i<br />
γ (n)<br />
j<br />
=<br />
= y n + h<br />
ν∑<br />
j=1<br />
a ij f(t j + c j h, K (n)<br />
j<br />
, γ (n)<br />
j<br />
) (7.76)<br />
{<br />
γ (n)<br />
j<br />
= g(t n + c j h − τ) if n < ν<br />
K (n−ν)<br />
j<br />
y n = y n−1 +<br />
ν∑<br />
j=1<br />
if n ≥ ν<br />
(7.77)<br />
b j f(t n−1 + c j h, K (n−1)<br />
j<br />
, γ (n−1)<br />
j<br />
) (7.78)<br />
This is equivalent to solving a different set of ordinary differential equations on each<br />
interval: on the interval [t 0 , t 0 + τ], solve<br />
On the interval [t 0 + τ, t 0 + 2τ], solve<br />
On the interval [t 0 + 2τ, t 0 + 3τ], solve<br />
u ′ (t) = f(t, u(t), g(t − τ)) (7.79)<br />
u ′ (t) = f(t, u(t), v(t)) (7.80)<br />
v ′ (t) = f(t − τ, v(t), g(t − 2τ)) (7.81)<br />
u ′ (t) = f(t, u(t), v(t)) (7.82)<br />
v ′ (t) = f(t − τ, v(t), w(t)) (7.83)<br />
w ′ (t) = f(t − 2τ, w(t), g(t − 3τ)) (7.84)<br />
c○2007, B.E.<strong>Shapiro</strong><br />
Last revised: May 23, 2007<br />
Math 582B, Spring 2007<br />
California State University Northridge