Game Development Reference
In-Depth Information
Runge-Kutta methods having a greater number of stages are derived in a
manner similar to that used to derive the two-stage method, except that higher-
order Taylor series expansions are equated. Without concerning ourselves with
the details of the long and uninteresting derivation, we state a popular four-stage
Runge-Kutta method, often called the RK4 method , as follows.
h
[
]
y
=+
y
Kxy
(
,
)
+
2
Kxy
(
,
)
+
2
Kxy
(
,
)
+
Kxy
(
,
)
(16.80)
i
+
1
i
1
i
i
2
i
i
3
i
i
4
i
i
6
(
)
(
)
xy
,
=
fxy
h
,
K
1
i
i
i
i
h
(
)
(
)
K
xy
,
=
f x
+
,
y
+
K xy
,
2
i
i
i
i
1
i
i
2
2
(16.81)
h
h
K
(
xy
,
)
=
f x
+
,
y
+
K xy
(
,
)
3
i
i
i
i
2
i
i
2
2
(
)
(
(
)
)
K
xy
,
=
fx hy hK xy
+
,
+
,
4
i
i
i
i
3
i
i
The RK4 method is usually more than adequate for the types of real-time simula-
tions encountered in a 3D game application. The calculation of Equation (16.80)
is very straightforward and also rather efficient for the accuracy that the RK4
method provides.
16.4.4 Higher-Order Differential Equations
We mentioned earlier that a higher-order differential equation could be trans-
formed into a system of first-order differential equations, allowing us to solve it
numerically using the methods already presented. First, let us consider a second-
order differential equation
′′
()
(
)
y
xf
=
xyy
,,
.
(16.82)
This can be expressed as the following pair of first-order equations.
y xzx
zx
()
=
()
()
(
)
=
fxyz
,,
(16.83)
()
()
Given initial conditions
, we can solve this system us-
ing Euler's method by applying the following step formula.
y x
=
y
and
zx
=
z
0
0
0
0
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