Two common models lead to first-order differential equations with stable equilibrium values. A logistic population approaches its carrying capacity, while a falling object's velocity approaches its terminal velocity.
Logistic population growth
Let N(t) be a population at time t. A population-dependent growth model has the form
dtdN=R(N)N,
where R(N) is the per-capita growth rate. To model limited resources, introduce a carrying capacityK>0. At zero population, the per-capita rate should equal the positive constant r; at capacity, it should vanish:
R(0)=r>0,R(K)=0.
It should also have the sign pattern
R(N)>0when 0<N<K,
so the population grows below capacity, and
R(N)<0when N>K,
so it decreases above capacity. At capacity, R(K)=0.
The simplest function with this sign pattern is the decreasing line
R(N)=r(1−KN)=Kr(K−N),r>0.
Substituting it into the population model gives the logistic equation:
dtdN=Kr(K−N)N.
It is first order, nonlinear because of the N2 term, and separable.
Per-capita growth rate
Growth is positive below the carrying capacity K, zero at K, and negative above K.
Population trajectories
K is a stable equilibrium: every positive trajectory shown approaches the carrying capacity.
Two D3 graphs showing how the logistic model changes sign at carrying capacity K and how positive solutions approach K.
Solving the logistic equation
For a nonconstant solution with N=0 and N=K, separate the variables:
N(K−N)KdN=rdt.
The partial-fraction decomposition is
N(K−N)K=N1+K−N1.
The second antiderivative has a minus sign because the derivative of K−N is −1:
∫(N1+K−N1)dN=ln∣N∣−ln∣K−N∣=lnK−NN.
Therefore,
lnK−NN=rt+C,
and the sign can be absorbed into one arbitrary constant C1:
K−NN=C1ert.
If N(0)=N0 and N0=K, then
C1=K−N0N0.
Solving for N gives
N(t)=N0+(K−N0)e−rtKN0.
This formula describes the nonconstant positive solutions. The values excluded during separation must be checked separately. They give the two equilibrium solutions
N(t)≡0andN(t)≡K.
For r>0:
if 0<N0<K, then N(t) increases toward K;
if N0=K, then N(t) stays at K;
if N0>K, then N(t) decreases toward K.
Thus K is both the carrying capacity and the stable positive equilibrium.
A falling object with linear drag
Take downward as the positive direction. Let:
v(t) be the downward velocity;
m>0 be the object's mass;
g>0 be gravitational acceleration;
γ>0 be the linear drag coefficient.
Gravity contributes +mg, while drag opposes the velocity and contributes −γv. Newton's second law gives
mv′(t)=mg−γv(t),
or
v′(t)=g−mγv(t).
This is a first-order linear equation. Put it in standard form:
v′+mγv=g.
Its integrating factor is
μ(t)=eγt/m.
Multiplying the equation by μ creates a product derivative:
dtd(eγt/mv(t))=geγt/m.
Integrating gives
eγt/mv(t)=γmgeγt/m+C.
If v(0)=v0, then C=v0−mg/γ, so
v(t)=γmg+(v0−γmg)e−γt/m.
Velocity under linear drag
The exponential term decays, so every curve approaches the terminal velocity mg/γ.
Since m>0 and γ>0,
e−γt/m⟶0as t→∞.
Therefore,
t→∞limv(t)=γmg.
The value mg/γ is the terminal velocity. It is also a stable equilibrium:
an initial velocity above mg/γ decreases toward it;
an initial velocity below mg/γ, including a negative one, increases toward it;
an initial velocity equal to mg/γ remains constant.