Unit 3, lesson 14

Autonomous Equations and Phase-Line Stability

How to read the long-term behavior of an autonomous equation from the sign of its rate, with equilibrium solutions, the phase line, stability, asymptotic stability, semistability and the derivative test.

  • Video 14
  • Phase Lines and Stability

Suppose a quantity yy changes at the rate y(2−y)y(2 - y), whatever the time on the clock. Will a start at y=0.1y = 0.1 drift away from 00, and where will it end up? Questions like these can be answered without a formula for the solution, by reading the sign of the rate on each side of the constant solutions. This lesson builds that picture, the phase line, and gives precise meanings to stable, asymptotically stable and semistable equilibria.

Key terms

Autonomous equation

Definition With tt as the independent variable and y′=dy/dty' = dy/dt, a first-order equation is autonomous if it has the form

y′=f(y),y' = f(y),

where the rate ff depends on the state yy alone and not on tt. Throughout this lesson ff is continuously differentiable on the real line, so every initial-value problem has exactly one solution on its maximal interval. A number y∗y_* with f(y∗)=0f(y_*) = 0 is an equilibrium, and the constant function y(t)=y∗y(t) = y_* for all tt is then a solution, called an equilibrium solution. Conversely, a constant solution y(t)=cy(t) = c has 0=y′=f(c)0 = y' = f(c), so the equilibrium solutions are exactly the constant solutions. Because ff does not involve tt, if y(t)y(t) is a solution then so is y(t−t0)y(t - t_0) for every constant t0t_0, and starting the clock at t=0t = 0 loses nothing.

In plain words The rule for change looks only at where the state is now, never at the clock. The states where the rate is zero are states that never change.

Example The equation y′=y(2−y)y' = y(2 - y) is autonomous, with f(y)=y(2−y)f(y) = y(2 - y). Its equilibria are the zeros of ff, namely 00 and 22, so y(t)=0y(t) = 0 and y(t)=2y(t) = 2 are equilibrium solutions. The equation y′=t−yy' = t - y is not autonomous, because the rate at the state y=1y = 1 is t−1t - 1, which changes with time. It has no equilibrium solution at all, since a constant y=cy = c would need 0=t−c0 = t - c for every tt.

Phase line

Definition The phase line of y′=f(y)y' = f(y) is the yy-axis with every equilibrium marked and, on each open interval between neighboring equilibria, an arrow toward larger yy where f>0f > 0 and toward smaller yy where f<0f < 0. The axis carries states, not times, and the arrows show only direction, not speed. Since ff is continuously differentiable, two different solutions never share a point, so no solution can cross or touch an equilibrium solution. A solution that starts in one of these open intervals therefore stays in it, moves strictly in the direction of the arrow for as long as it exists, and never reaches an equilibrium at a finite time. If an equilibrium lies at the head of the arrow, the solution exists for all t≥0t \ge 0 and tends to that equilibrium as t→∞t \to \infty. If the interval has no end in that direction, the solution is unbounded in that direction, and it may become infinite at a finite time.

In plain words Mark where the rate is zero, test the sign of the rate once in each gap, and draw arrows. Every nonconstant solution slides along its gap in the direction of the arrow and can approach the equilibrium ahead of it, but never reach it.

Example For f(y)=y(2−y)f(y) = y(2 - y), one sample value in each interval gives the signs.

IntervalSample valueSign of ffArrow
y<0y < 0f(−1)=−3f(-1) = -3negativedown
0<y<20 < y < 2f(1)=1f(1) = 1positiveup
y>2y > 2f(3)=−3f(3) = -3negativedown

With the axis drawn vertically, the arrows point away from 00 and toward 22. The start y(0)=1y(0) = 1 gives the solution

y(t)=21+e−2t,y(t) = \frac{2}{1 + e^{-2t}},

which is defined for all tt and rises toward 22 without reaching it. Differentiating gives

y′(t)=4e−2t(1+e−2t)2,y'(t) = \frac{4e^{-2t}}{(1 + e^{-2t})^2},

and since 2−y=2e−2t/(1+e−2t)2 - y = 2e^{-2t}/(1 + e^{-2t}), the product y(2−y)y(2 - y) is the same expression. The start y(0)=−1y(0) = -1 gives y(t)=2/(1−3e−2t)y(t) = 2/(1 - 3e^{-2t}), which decreases and tends to −∞-\infty as tt increases to (ln⁡3)/2≈0.549(\ln 3)/2 \approx 0.549.

Stable and unstable equilibria

Definition An equilibrium y∗y_* of y′=f(y)y' = f(y) is stable if for every ε>0\varepsilon > 0 there is a δ>0\delta > 0 such that every solution with ∣y(0)−y∗∣<δ\lvert y(0) - y_* \rvert < \delta is defined for all t≥0t \ge 0 and satisfies ∣y(t)−y∗∣<ε\lvert y(t) - y_* \rvert < \varepsilon for all t≥0t \ge 0. An equilibrium that is not stable is unstable. Then for some ε>0\varepsilon > 0 there are starts as close to y∗y_* as we like whose solutions later leave the interval (y∗−ε,y∗+ε)(y_* - \varepsilon, y_* + \varepsilon). When only part of the axis is meaningful, such as y≥0y \ge 0 for a population, stability relative to that domain uses the same definition with the starts restricted to the domain, and the scope has to be stated.

In plain words Stability is about staying close. Whatever distance is demanded, a start close enough to the equilibrium keeps the solution within that distance for all future time, and a tighter demand may need a closer start.

Example For y′=y(2−y)y' = y(2 - y) the equilibrium 22 is stable. A start with ∣y(0)−2∣<2\lvert y(0) - 2 \rvert < 2 lies in (0,4)(0, 4), where the arrows point toward 22, so the distance to 22 never grows, and δ=min⁡(ε,2)\delta = \min(\varepsilon, 2) works. The equilibrium 00 is unstable. Take ε=1\varepsilon = 1. Every start in (0,1)(0, 1), however close to 00, rises toward 22 and reaches y=1y = 1 at some time, so no δ\delta works.

Asymptotic stability

Definition An equilibrium y∗y_* is asymptotically stable if it is stable and there is an η>0\eta > 0 such that every solution with ∣y(0)−y∗∣<η\lvert y(0) - y_* \rvert < \eta satisfies y(t)→y∗y(t) \to y_* as t→∞t \to \infty. The set of all starts whose solutions tend to y∗y_* is its basin of attraction. On a phase line, an equilibrium with arrows pointing toward it from both sides is asymptotically stable.

In plain words Asymptotic stability asks for more than staying close. Nearby solutions must also settle onto the equilibrium as time goes on.

Example For y′=y(2−y)y' = y(2 - y) the arrows point toward 22 from both sides, and every start y(0)>0y(0) > 0 gives a solution with y(t)→2y(t) \to 2, so 22 is asymptotically stable with basin (0,∞)(0, \infty). For y′=0y' = 0 every number cc is an equilibrium. Each one is stable, with δ=ε\delta = \varepsilon, because every solution is constant. None is asymptotically stable, because a start at c+0.01c + 0.01 stays at c+0.01c + 0.01 forever.

Derivative test for equilibria

Definition Let y∗y_* be an equilibrium of y′=f(y)y' = f(y), with ff continuously differentiable on an open interval containing y∗y_*. If f′(y∗)<0f'(y_*) < 0, then y∗y_* is asymptotically stable. If f′(y∗)>0f'(y_*) > 0, then y∗y_* is unstable. If f′(y∗)=0f'(y_*) = 0, the test gives no conclusion. The reason is the mean value theorem. Since f(y∗)=0f(y_*) = 0, we have f(y)=f′(c)(y−y∗)f(y) = f'(c)(y - y_*) for some cc between y∗y_* and yy, and when f′(y∗)≠0f'(y_*) \ne 0 continuity keeps f′(c)f'(c) of the same sign as f′(y∗)f'(y_*) for yy near y∗y_*. So the arrows next to y∗y_* point toward it when f′(y∗)<0f'(y_*) < 0 and away from it when f′(y∗)>0f'(y_*) > 0.

In plain words Near an equilibrium the rate looks like a line through it with slope f′(y∗)f'(y_*). A falling line sends nearby states back, a rising line pushes them away, and a slope of zero says nothing, so the sign of ff itself has to be checked.

Example For f(y)=y(2−y)f(y) = y(2 - y) the derivative is f′(y)=2−2yf'(y) = 2 - 2y. It gives f′(0)=2>0f'(0) = 2 > 0 and f′(2)=−2<0f'(2) = -2 < 0, so 00 is unstable and 22 is asymptotically stable, as the phase line showed. The test is inconclusive at 00 for each of y′=−y3y' = -y^3, y′=y3y' = y^3, y′=y2y' = y^2 and y′=0y' = 0, since all four rates have derivative 00 there. Their signs give four different answers. The equilibrium 00 is asymptotically stable for −y3-y^3, unstable for y3y^3, semistable for y2y^2, and stable but not asymptotically stable for the zero rate.

Semistability

Definition An equilibrium y∗y_* of y′=f(y)y' = f(y) is semistable if, for some δ>0\delta > 0, the rate ff has the same strict sign on (y∗−δ,y∗)(y_* - \delta, y_*) and on (y∗,y∗+δ)(y_*, y_* + \delta). Both arrows next to y∗y_* then point the same way. If f>0f > 0 on both sides, solutions just below y∗y_* rise toward it and solutions just above rise away from it, and if f<0f < 0 on both sides the roles are reversed. A semistable equilibrium is unstable on the full line, although relative to its attracting side alone it is asymptotically stable.

In plain words A semistable equilibrium attracts from one side and repels on the other, so a small push to the wrong side is never corrected.

Example The equation y′=(y−1)2y' = (y - 1)^2 has the single equilibrium 11, and the rate is positive on both sides. The starts y(0)=0y(0) = 0 and y(0)=2y(0) = 2 give

y(t)=1−11+t,y(t)=1+11−t,\begin{gathered} y(t) = 1 - \frac{1}{1 + t}, \\[0.4em] y(t) = 1 + \frac{1}{1 - t}, \end{gathered}

with maximal intervals (−1,∞)(-1, \infty) and (−∞,1)(-\infty, 1). Each one solves the equation, since y′y' and (y−1)2(y - 1)^2 both equal 1/(1+t)21/(1 + t)^2 for the first and 1/(1−t)21/(1 - t)^2 for the second. The first rises toward 11 as t→∞t \to \infty. The second started at the same distance from the equilibrium, yet it moves away and becomes infinite as tt increases to 11. Because solutions are unique, no solution reaches 11 at a finite time and then leaves it. If only states y≤1y \le 1 were meaningful, the equilibrium 11 would be asymptotically stable relative to that domain.

Check yourself

  1. Draw the phase line of y′=y3−4yy' = y^3 - 4y, classify each equilibrium, and check the result with the derivative test. Where does the solution with y(0)=1y(0) = 1 go?
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Factoring gives f(y)=y(y−2)(y+2)f(y) = y(y - 2)(y + 2), so the equilibria are −2-2, 00 and 22. Sample values give f(−3)=−15f(-3) = -15, f(−1)=3f(-1) = 3, f(1)=−3f(1) = -3 and f(3)=15f(3) = 15. The arrows point away from −2-2 on both sides, toward 00 from both sides, and away from 22 on both sides. So −2-2 and 22 are unstable and 00 is asymptotically stable. The derivative f′(y)=3y2−4f'(y) = 3y^2 - 4 gives f′(−2)=8f'(-2) = 8, f′(0)=−4f'(0) = -4 and f′(2)=8f'(2) = 8, which agrees. The start y(0)=1y(0) = 1 lies in (0,2)(0, 2), where f<0f < 0, so the solution decreases toward 00 as t→∞t \to \infty without reaching it.

  1. For y′=y2(1−y)y' = y^2(1 - y) a classmate finds f′(0)=0f'(0) = 0 and concludes that 00 is stable. Classify both equilibria correctly.
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The equilibria are 00 and 11. Since f′(y)=2y−3y2f'(y) = 2y - 3y^2, the value f′(1)=−1f'(1) = -1 shows that 11 is asymptotically stable. At 00 the derivative is 00, so the test says nothing and the signs decide. The rate y2(1−y)y^2(1 - y) is positive for y<0y < 0 and for 0<y<10 < y < 1, so both arrows next to 00 point up. Solutions just below 00 rise toward it, and solutions just above rise away from it toward 11. So 00 is semistable, and therefore unstable. A zero derivative never proves stability.

  1. The equation y′=3y2/3y' = 3y^{2/3}, with the real cube root, has the equilibrium 00. Show that y(t)=t3y(t) = t^3 also solves it with y(0)=0y(0) = 0, and explain why this does not contradict the statement that a solution never reaches or leaves an equilibrium at a finite time.
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For y=t3y = t^3 we get y′=3t2y' = 3t^2 and 3y2/3=3(t3)2/3=3t23y^{2/3} = 3(t^3)^{2/3} = 3t^2, so it is a solution. So is the function equal to 00 for t≤0t \le 0 and to t3t^3 for t>0t > 0, which rests at the equilibrium and then leaves it at t=0t = 0. The statement assumed that ff is continuously differentiable, which guarantees unique solutions. Here f(y)=3y2/3f(y) = 3y^{2/3} is continuous, but its derivative 2y−1/32y^{-1/3} is unbounded near y=0y = 0 and does not exist at 00. Uniqueness fails at the equilibrium, and the phase-line conclusion that solutions never reach an equilibrium no longer applies.

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