11.5 Periodic Solutions, Limit Cycles, and Global Stability

INTRODUCTION

In this section we will investigate the existence of periodic solutions of nonlinear plane autonomous systems and introduce special periodic solutions called limit cycles.

We saw in Sections 11.3 and 11.4 that an analysis of critical points using linearization can provide valuable information on the behavior of solutions near critical points and insight into a variety of biological and physical phenomena. There are, however, some inherent limitations to this approach. When the eigenvalues of the Jacobian matrix are pure imaginary, we cannot conclude that there are periodic solutions near the critical point. In some cases we were able to solve dy/dx = Q(x, y)/P(x, y), obtain an implicit representation f(x, y) = c of the solution curves, and investigate whether any of these solutions formed closed curves. More often than not, this differential equation will not possess closed-form solutions. For example, the Lotka–Volterra competition model cannot be handled by this procedure. The first goal of this section is to determine conditions under which we can either exclude the possibility of periodic solutions or assert their existence.

We encountered an additional problem in studying the models in Section 11.3. FIGURE 11.5.1 illustrates the common situation in which a region R contains a single asymptotically stable critical point X1. We can assert that limt→∞ X(t) = X1 when the initial position X(0) = X0 is “near” X1, but under what conditions is limt→∞ X(t) = X1 for all initial positions in R? Such a critical point is called globally stable in R. A second goal is to determine conditions under which an asymptotically stable critical point is globally stable.

A region R is bound by a closed curve and shaded. Two points X subscript 0 and X subscript 1 are marked with black dots inside the region. A curved arrow starts from X subscript 0 and approaches X subscript 1 and is labeled with a question mark.

FIGURE 11.5.1 For any X0 in R, does X approach X1 as t → ∞?

In motivating and discussing the methods in this section, we will use the fact that the vector field V(x, y) = (P(x, y), Q(x, y)) can be interpreted as defining a fluid flow in a region of the plane, and a solution to the autonomous system may be interpreted as the resulting path of a particle as it moves through the region.

Negative Criteria

A number of results can sometimes be used to establish that there are no periodic solutions in a given region R of the plane. We will assume that P(x, y) and Q(x, y) have continuous first partial derivatives in R and that R is simply connected. Recall that in a simply connected region, any simple closed curve C in R encloses only points in R. Therefore, if there is a periodic solution X = X(t) in R, then R will contain all points in the interior of the resulting curve.

THEOREM 11.5.1 Cycles and Critical Points

If a plane autonomous system has a periodic solution X = X(t) in a simply connected region R, then the system has at least one critical point inside the corresponding simple closed curve C. If there is a single critical point inside C, then that critical point cannot be a saddle point.

  Corollary to Theorem 11.5.1

If a simply connected region R either contains no critical points of a plane autonomous system or contains a single saddle point, then there are no periodic solutions in R.

EXAMPLE 1 No Periodic Solutions

Show that the plane autonomous system

has no periodic solutions.

SOLUTION

If (x, y) is a critical point, then, from the first equation, either x = 0 or y = 0. If x = 0, then –1 – y2 = 0 or y2 = –1. Likewise, y = 0 implies x2 = –1. Therefore, this plane autonomous system has no critical points, and by the corollary possesses no periodic solutions in the plane.

EXAMPLE 2 Lotka–Volterra Competition Model

Show that the Lotka–Volterra competition model

x′ = 0.004x(50 – x – 0.75y)

y′ = 0.001y(100 – y – 3.0x)

has no periodic solutions in the first quadrant.

SOLUTION

In Example 4 in Section 11.4 we showed that this system has critical points at (0, 0), (50, 0), (0, 100), and (20, 40), and that (20, 40) is a saddle point. Since only (20, 40) lies in the first quadrant, by the corollary there are no periodic solutions in the first quadrant.

Another sometimes useful result can be formulated in terms of the divergence of the vector field V(x, y) = (P(x, y), Q(x, y)):

THEOREM 11.5.2 Bendixson Negative Criterion

If div V = ∂P/∂x + ∂Q/∂y does not change sign in a simply connected region R, then the plane autonomous system has no periodic solutions in R.

PROOF:

Suppose, to the contrary, that there is a periodic solution X = X(t) lying in R, and let C be the resulting simple closed curve and R1 the region bounded by C. Green’s theorem states that

whenever M(x, y) and N(x, y) have continuous first partials in R. If we let N = P and M = –Q, we obtain

Since X = X(t) is a solution with period p, we have x′(t) = P(x(t), y(t)) and y′(t) = Q(x(t), y(t)), and so

Since div V = ∂P/∂x + ∂Q/∂y is continuous and does not change sign in R, it follows that either div V ≥ 0 in R or div V ≤ 0 in R, and so

This contradiction establishes that there are no periodic solutions in R.

EXAMPLE 3 Bendixson Negative Criterion

Investigate possible periodic solutions of each system.

SOLUTION

(a) We have div V = ∂P/∂x + ∂Q/∂y = 1 + 12x2 + 2 + x2 + 3y2 ≥ 3, and so there are no periodic solutions in the plane.

(b) For this system div V = (2 – 3x2y2) + (2 – x2 – 3y2) = 4 – 4(x2 + y2). Therefore, if R is the interior of the circle x2 + y2 = 1, div V > 0, and so there are no periodic solutions inside this disk. Note that div V < 0 on the exterior of the circle. If R is any simply connected subset of the exterior, then there are no periodic solutions in R. It follows that if there is a periodic solution in the exterior, it must enclose the circle x2 + y2 = 1. In fact, the reader can verify that X(t) = ( sin t, cos t) is a periodic solution that generates the circle x2 + y2 = 2.

EXAMPLE 4 Sliding Bead and Periodic Solutions

The sliding bead discussed in Section 11.4 satisfies the differential equation

Show that there are no periodic solutions.

SOLUTION

The corresponding plane autonomous system is

and so div V = By Theorem 11.5.2 we conclude the system has no periodic solutions.

The following theorem is a generalization of the Bendixson negative criterion, which leaves it to the reader to construct an appropriate function δ(x, y).

THEOREM 11.5.3 Dulac Negative Criterion

If δ (x, y) has continuous first partial derivatives in a simply connected region R and does not change sign in R, then the plane autonomous system has no periodic solutions in R.

There are no general techniques for constructing an appropriate function δ(x, y). Instead, we experiment with simple functions of the form ax2 + by2, eax+by, xayb, and so on, and try to determine constants for which (δP)/∂x + (δQ)/∂y is nonzero in a given region.

EXAMPLE 5 Dulac Negative Criterion

Show that the second-order nonlinear differential equation

x″ = x2 + (x′)2xx′

has no periodic solutions.

SOLUTION

The corresponding plane autonomous system is

If we let δ(x, y) = eax+by, then

If we set a = –2 and b = 0, then (δP)/∂x + (δQ)/∂y = –eax+by, which is always negative. Therefore, by the Dulac negative criterion, the second-order differential equation has no periodic solutions.

EXAMPLE 6 Dulac Negative Criterion

Use δ(x, y) = 1/(xy) to show that the Lotka–Volterra competition equations

have no periodic solutions in the first quadrant.

SOLUTION

If δ(x, y) = 1/(xy), then

and so

For (x, y) in the first quadrant, the latter expression is always negative. Therefore, there are no periodic solutions.

Positive Criteria: Poincaré–Bendixson Theory

The Poincaré–Bendixson theorem is an advanced result that describes the long-range behavior of a bounded solution to a plane autonomous system. Rather than present the result in its full generality, we will concentrate on a number of special cases that occur frequently in applications. One of these cases will lead to a new type of periodic solution called a limit cycle.

DEFINITION 11.5.1 Invariant Region

A region R is called an invariant region for a plane autonomous system if, whenever X0 is in R, the solution X = X(t) satisfying X(0) = X0 remains in R.

FIGURE 11.5.2 shows two standard types of invariant regions. A Type I invariant region R is bounded by a simple closed curve C, and the flow at the boundary defined by the vector field V(x, y) = (P(x, y), Q(x, y)) is always directed into the region. This prevents a particle from crossing the boundary. A Type II invariant region is an annular region bounded by simple closed curves C1 and C2, and the flow at the boundary is again directed toward the interior of R. The following theorem provides a method for verifying that a given region is invariant.

Two images. A. A region R is shaded and bound by a closed curve C. A vector field is represented by arrows from the curve point inward and to the right. A vector V points down and to the right, vector n points down vertically. The angle between vector n and vector V is theta. B. A region R is shaded and bound by a closed curve C subscript 1 and a small curve C subscript 2 within C subscript 1. A vector field is represented by arrows from the curve point inward and to the right. A vector V points down and to the right, vector n points down vertically. The angle between vector n and vector V is theta. A vector field with arrows go up and to the left from C subscript 2.

FIGURE 11.5.2 Two types of invariant regions

THEOREM 11.5.4 Normal Vectors and Invariant Regions

If n(x, y) denotes a normal vector on the boundary that points inside the region, then R will be an invariant region for the plane autonomous system provided V(x, y) ⋅ n(x, y) ≥ 0 for all points (x, y) on the boundary.

PROOF:

If θ is the angle between V(x, y) and n(x, y), then from Vn = ∥V∥ ∥n∥ cos θ, we may conclude that cos θ ≥ 0 and so θ is between 0° and 90°. The flow is therefore directed into the region (or at worst along the boundary) for any boundary point (x, y). This prevents a solution that starts in R from leaving R. Therefore, R is an invariant region for the plane autonomous system.

The problem of finding an invariant region for a given nonlinear system is an extremely difficult one. An excellent first step is to use software that plots the vector field V(x, y) = (P(x, y), Q(x, y)) together with the curves P(x, y) = 0 (along which the vectors are vertical) and Q(x, y) = 0 (along which the vectors are horizontal). This can lead to choices for R. In the following examples, we will construct invariant regions bounded by lines and circles. In more complicated cases, we will be content to offer empirical evidence that an invariant region exists.

EXAMPLE 7 Circular Invariant Region

Find a circular region with center at (0, 0) that serves as an invariant region for the plane autonomous system

x′ = –yx3

y′ = xy3.

SOLUTION

For the circle x2 + y2 = r2, n = (–2x, –2y) is a normal vector that points toward the interior of the circle. Since

Vn = (–yx3, xy3) ⋅ (–2x, –2y) = 2(x4 + y4),

we may conclude that Vn ≥ 0 on the circle x2 + y2 = r2. Therefore, by Theorem 11.5.4 the circular region defined by x2 + y2r2 serves as an invariant region for the system for any r > 0.

EXAMPLE 8 Annular Invariant Region

Find an annular region bounded by circles that serves as an invariant region for the plane autonomous system

x′ = xy – 5x(x2 + y2) + x5

y′ = x + y – 5y(x2 + y2) + y5.

SOLUTION

As in Example 7, the normal vector n1 = (–2x, –2y) points inside the circle x2 + y2 = r2, while the normal vector n2 = –n1 is directed toward the exterior. Computing Vn1 and simplifying, we obtain

Vn1 = –2(r2 – 5r4 + x6 + y6).

Note that r2 – 5r4 = r2(1 – 5r2) takes on both positive and negative values.

If r = 1, Vn1 = 8 – 2(x6 + y6) ≥ 0, since the maximum value of x6 + y6 on the circle x2 + y2 = 1 is 1. The flow is therefore directed toward the interior of the circular region x2 + y2 ≤ 1.

If r = , Vn1 ≤ –2(r2 – 5r4) < 0, and so Vn2 = –Vn1 > 0. The flow is therefore directed toward the exterior of the circle x2 + y2 = , and so the annular region R defined by is an invariant region for the system.

EXAMPLE 9 The Van der Pol Equation

The Van der Pol equation is a nonlinear second-order differential equation that arises in electronics, and as a plane autonomous system it takes the form

FIGURE 11.5.3 shows the corresponding vector field for µ = 1, together with the curves y = 0 and (x2 – 1)y = –x along which the vectors are vertical and horizontal, respectively. (For convenience we have sketched the normalized vector field V/∥V∥.) It is not possible to find a simple invariant region whose boundary consists of lines or circles. The figure does offer empirical evidence that an invariant region R, with (0, 0) in its interior, does exist. Advanced methods are required to demonstrate this mathematically.*

Three curves are graphed on an x y plane. The first curve enters the left of the second quadrant, goes up and to the right, and exits the top of the second quadrant. It is labeled P greater than 0, Q greater than 0. The second curve enters the bottom of the third quadrant, goes up and to the right through the origin, and exits the top of the first quadrant. The part of the curve in the third quadrant is labeled P less than 0, Q greater than 0. The part of the curve in the first quadrant is labeled P greater than 0, Q less than 0. The third curve enters the bottom of the fourth quadrant, goes up and to the right, and exits the right of the fourth quadrant. It is labeled P less than 0, Q less than 0. Arrows in the entire plane region represent vector field. Vertical upward arrows are shown away from the curve in the third quadrant. Vertical downward arrows are shown away from the curve in the first quadrant. Horizontal arrows are seen close to the curves. Arrows from the right and left are seen approaching toward the concave surface of the curves and they are seen moving away from the convex surface of the curves.

FIGURE 11.5.3 Vector field for Van der Pol’s equation in Example 9

We next present two important special cases of the Poincaré–Bendixson theorem that guarantee the existence of periodic solutions.

THEOREM 11.5.5 Poincaré–Bendixson I

Let R be an invariant region for a plane autonomous system and suppose that R has no critical points on its boundary.

  1. If R is a Type I region that has a single unstable node or an unstable spiral point in its interior, then there is at least one periodic solution in R.
  2. If R is a Type II region that contains no critical points of the system, then there is at least one periodic solution in R.

In either of the two cases, if X = X(t) is a nonperiodic solution in R, then X(t) spirals toward a cycle that is a solution to the system. This periodic solution is called a limit cycle.

The flow interpretation portrayed in Figure 11.5.2 can be used to make the result plausible. If a particle is released at a point X0 in a Type II invariant region R, then, with no escape from the region and with no resting points, the particle will begin to rotate around the boundary C2 and settle into a periodic orbit. It is not possible for the particle to return to an earlier position unless the solution is itself periodic.

EXAMPLE 10 Existence of a Periodic Solution

Use Theorem 11.5.5 to show that the system

  x′ = –y + x(1 – x2y2) – y(x2 + y2)

y′ = x + y(1 – x2y2) + x(x2 + y2)

has at least one periodic solution.

SOLUTION

We first construct an invariant region that is bounded by circles. If n1 = (–2x, –2y), then Vn1 = –2r2(1 – r2). If we let r = 2 and then r = , we may conclude that the annular region R defined by x2 + y2 ≤ 4 is invariant. If (x1, y1) is a critical point of the system, then Vn1 = (0, 0) ⋅ n1 = 0. Therefore, r = 0 or r = 1. If r = 0, then (x1, y1) = (0, 0) is a critical point. If r = 1, the system reduces to –2y = 0, 2x = 0, and we have reached a contradiction. Therefore, (0, 0) is the only critical point, and this critical point is not in R. By part (b) of Theorem 11.5.5, the system has at least one periodic solution in R.

The reader can verify that X(t) = (cos 2t, sin 2t) is a periodic solution.

EXAMPLE 11 Limit Cycle in the Van der Pol Equation

Show that the Van der Pol differential equation

x″ + µ(x2 – 1)x′ + x = 0

has a periodic solution when µ > 0.

SOLUTION

We will assume that there is a Type I invariant region R for the corresponding plane autonomous system and that this region contains (0, 0) in its interior (see Example 9 and Figure 11.5.3). The only critical point is (0, 0), and the Jacobian matrix is given by

Therefore, τ = µ, Δ = 1, and τ2 – 4Δ = µ2 – 4. Since µ > 0, the critical point is either an unstable spiral point or an unstable node. By part (a) of Theorem 11.5.5, the system has at least one periodic solution in R. FIGURE 11.5.4 shows solutions corresponding to X(0) = (0.5, 0.5) and X(0) = (3, 3) for µ = 1. Each of these solutions spirals around the origin and approaches a limit cycle. It can be shown that the Van der Pol differential equation has a unique limit cycle for all values of the parameter µ.

Two curves are graphed on an x y plane. The first curve starts from the point (0.5, 0.5) marked with a dot, spirals around the origin through all the four axes, and approaches a cycle at a point in the first quadrant. The second curve starts from the point (3, 3) marked with a dot, spirals around the origin through all the four axes, and approaches the same cycle as the first curve at a point in the third quadrant.

FIGURE 11.5.4 Two solutions of Van der Pol’s equation approaching the same limit cycle in Example 11

Global Stability

Another version of the Poincaré–Bendixson theorem can be used to show that a locally stable critical point is globally stable:

THEOREM 11.5.6 Poincaré–Bendixson II

Let R be a Type I invariant region for a plane autonomous system that has no periodic solutions in R.

  1. If R has a finite number of nodes or spiral points, then given any initial position X0 in R, limt→∞ X(t) = X1 for some critical point X1.
  2. If R has a single stable node or stable spiral point X1 in its interior and no critical points on its boundary, then limt→∞ X(t) = X1 for all initial positions X0 in R.

In Theorem 11.5.6 the particle cannot escape from R, cannot return to any of its prior positions, and therefore, in the absence of cycles, must be attracted to some stable critical point X1.

EXAMPLE 12 A Globally Stable Critical Point

Investigate global stability for the system from Example 7:

x′ = –yx3

y′ = xy3.

SOLUTION

In Example 7 we showed that the circular region defined by x2 + y2r2 serves as an invariant region for the system for any r > 0. Since ∂P/∂x + ∂Q/∂y = –3x2 – 3y2 does not change sign, there are no periodic solutions by the Bendixson negative criterion. It is not hard to show that (0, 0) is the only critical point and that the Jacobian matrix is

Since τ = 0 and Δ = 1, (0, 0) may be either a stable or an unstable spiral (it cannot be a center). Theorem 11.5.6, however, guarantees that limt→∞ X(t) = X1 for some critical point X1. Since (0, 0) is the only critical point, we must have limt→∞ X(t) = (0, 0) for any initial position X0 in the plane. The critical point is therefore a globally stable spiral point. FIGURE 11.5.5 shows two views of the solution satisfying X(0) = (4, 4). Figure 11.5.5(b) is an enlarged view of the curve around (0, 0). Notice how slowly the solution spirals toward (0, 0).

Two graphs. Graph (a) has the normal view of a solution curve. The curve is graphed on an x y plane. It starts from the point (4, 4) marked with a dot and spirals in toward the origin. Graph (b) has the enlarged view of the curve around the origin. The curve spirals in slowly toward the origin and becomes a circular cycle around the origin.

FIGURE 11.5.5 Zoom-in of a region around (0, 0) in Example 12

11.5 Exercises Answers to selected odd-numbered problems begin on page ANS-31.

In Problems 1–8, show that the given plane autonomous system (or second-order differential equation) has no periodic solutions.

  1. x′ = 2 + xy
    y′ = xy
  2. x′ = 2xxy
    y′ = –1 – x2 + 2xy2
  3. x′ = –x + y2
    y′ = xy
  4. x′ = xy2x2y
    y′ = x2y – 1
  5. x′ = –µxy
    y′ = x + y3
    for µ < 0
  6. x′ = 2x + y2
    y′ = xyy
  7. x″ – 2x + (x′)4 = 0
  8. x″ + x = [ + 3(x′)2]x′x2

In Problems 9 and 10, use the Dulac negative criterion to show that the given plane autonomous system has no periodic solutions. Experiment with simple functions of the form δ(x, y) = ax2 + by2, eax+by, or xayb.

  1. x′ = –2x + xy
    y′ = 2yx2
  2. x′ = –x3 + 4xy
    y′ = –5x2y2
  3. Show that the plane autonomous system

    x′ = x(1 – x2 – 3y2)

    y′ = y(3 – x2 – 3y2)

    has no periodic solutions in an elliptical region about the origin.

  4. If ∂g/∂x′ ≠ 0 in a region R, prove that x″ = g(x, x′) has no periodic solutions in R.
  5. Show that the predator–prey model

    in Problem 20 of Exercises 11.4 has no periodic solutions in the first quadrant.

In Problems 14 and 15, find a circular invariant region for the given plane autonomous system.

  1. x′ = –yxex+y
    y′ = xyex+y
  2. x′ = –x + y + xy
    y′ = xyx2y3
  3. Verify that the region bounded by the closed curve x6 + 3y2 = 1 is an invariant region for the second-order nonlinear differential equation x″ + x′ = –(x′)3x5. See FIGURE 11.5.6.
    A closed curve is graphed on an x y plane. The curve is in the form of a rectangle with rounded edges centered at the origin. The region inside the curve is shaded. The curve is labeled x^6 + 3 y^2 equals 1. The length of the rectangle is 1 unit to the left of the y axis and 1 unit to the right of the y axis. The width of the rectangle is approximately 0.577 unit above the x axis and approximately 0.577 unit below the x axis.

    FIGURE 11.5.6 Invariant region in Problem 16

  4. The plane autonomous system in Example 8 has only one critical point. Can we conclude that this system has at least one periodic solution?
  5. Use the Poincaré–Bendixson theorem to show that the second-order nonlinear differential equation

    x″ = x′[1 – 3x2 – 2(x′)2] – x

    has at least one periodic solution. [Hint: Find an invariant annular region for the corresponding plane autonomous system.]

  6. Let X = X(t) be the solution of the plane autonomous system

    that satisfies X(0) = (x0, y0). Show that if + < 1, then limt→∞ X(t) = (0, 0). [Hint: Select r < 1 with + < r2 and first show that the circular region R defined by x2 + y2r2 is an invariant region.]

  7. Investigate global stability for the system

    x′ = yx

    y′ = –xy3.

  8. Empirical evidence suggests that the plane autonomous system

    has a Type I invariant region R that lies inside the rectangle defined by 0 ≤ x ≤ 2, 0 ≤ y ≤ 1.

    1. Use the Bendixson negative criterion to show that there are no periodic solutions in R.
    2. If X0 is in R and X = X(t) is the solution satisfying X(t) = X0, use Theorem 11.5.6 to find limt→∞ X(t).
    1. Find and classify all critical points of the plane autonomous system

    2. FIGURE 11.5.7 shows the vector field V/∥V∥ and offers empirical evidence that there is an invariant region R in the first quadrant with a critical point in its interior. Assuming that such a region exists, prove that there is at least one periodic solution.
      A curve is graphed on an x y plane. It starts from the point (2, 6) marked with a dot, spirals in clockwise within the first quadrant, and ends at a point that corresponds to the y value of 2. Arrows representing vector field are seen in the entire region of the first quadrant. The arrows within the curve spirals around counter clockwise. The arrows outside the curve move away from the curve in counter clockwise direction. A horizontal line from (0, 2) passes through the endpoint of the curve. It is labeled x prime equals 0. A curve from (0, 8) goes down and to the right, then goes down and to the left, and ends at (1, 0). It is labeled y prime equals 0.

      FIGURE 11.5.7 Vector field in Problem 22

 

*See M. Hirsch and S. Smale, Differential Equations, Dynamical Systems, and Linear Algebra (New York: Academic Press, 1974).