Ch 9 7 periodic solutions and limit cycles
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Ch 9.7: Periodic Solutions and Limit Cycles. In this section we discuss further the possible existence of periodic solutions of second order autonomous systems x ' = f ( x )

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Ch 9 7 periodic solutions and limit cycles l.jpg
Ch 9.7: Periodic Solutions and Limit Cycles

  • In this section we discuss further the possible existence of periodic solutions of second order autonomous systems

    x' = f(x)

  • Such solutions satisfy the relation x(t + T) = x(t) for all t and for some nonnegative constant T called the period.

  • Periodic solutions are often important in physical problems because they represent phenomena that occur repeatedly.

  • In many situations a periodic solution represents a “final state” toward which all “neighboring” solutions tend as the transients due to the initial conditions die out.


Nonconstant periodic solutions l.jpg
Nonconstant Periodic Solutions

  • Thus a periodic solution satisfies x(t + T) = x(t) for all t and for some nonnegative constant T.

  • Note that a constant solution x = x0 is periodic for any T.

  • In this section, the periodic solutions that are discussed refer to nonconstant periodic solutions.

  • In this case the period T is positive and is usually chosen as the smallest positive number for which x(t + T) = x(t) is valid.


Linear autonomous systems l.jpg
Linear Autonomous Systems

  • Recall: The solutions of a linear autonomous system x' = Ax are periodic if and only if the eigenvalues are pure imaginary.

  • Thus if the eigenvalues of A are pure imaginary, then every solution of x' = Ax is periodic, while if the eigenvalues of A are not pure imaginary, then there are no periodic solutions.

  • The predator-prey equations discussed in Section 9.5, although nonlinear, behave similarly: All solutions in the first quadrant are periodic. See graph below.


Example 1 nonlinear system 1 of 8 l.jpg
Example 1: Nonlinear System (1 of 8)

  • Consider the nonlinear autonomous system

  • It can be shown that (0, 0) is the only critical point and that this system is almost linear near the origin.

  • The corresponding linear system

    has eigenvalues 1  i, and hence the origin is an unstable spiral point.


Example 1 unstable spiral point 2 of 8 l.jpg
Example 1: Unstable Spiral Point (2 of 8)

  • Thus the origin is an unstable spiral point, and hence any solution that starts near the origin in the phase plane will spiral away from the origin.

  • Since there are no other critical points, we might think that all solutions of our nonlinear system correspond to trajectories that spiral out to infinity.

  • However, we will show that this is incorrect, because far away from the origin the trajectories are directed inward.


Example 1 polar coordinates 3 of 8 l.jpg
Example 1: Polar Coordinates (3 of 8)

  • Our nonlinear system can be written as

  • Then

  • Using polar coordinates x = rcos and y = rsin, note that

  • Thus


Example 1 critical points for equation of radius 4 of 8 l.jpg
Example 1: Critical Points for Equation of Radius (4 of 8)

  • The critical points (for r  0) of

    are r = 0 (the origin) and r = 1, which corresponds to the unit circle in the phase plane.

  • Note that dr/dt > 0 if r < 1 and dr/dt < 0 if r > 1. Thus inside the unit circle, the trajectories are directed outward, while outside the unit circle they are directed inward.

  • The circle r = 1 appears to be a limiting trajectory for system.

  • We next determine an equation for .


Example 1 equation for angle 5 of 8 l.jpg
Example 1: Equation for Angle (5 of 8)

  • Recall our nonlinear system:

  • Then

  • Using polar coordinates x = rcos and y = rsin, note that

  • It follows that


Example 1 a solution to polar equations 6 of 8 l.jpg
Example 1: A Solution to Polar Equations (6 of 8)

  • Our original nonlinear system

    is therefore equivalent to the system

  • One solution to this system is

    where t0 is an arbitrary constant.

  • As t increases, a point on this solution trajectory moves clockwise around the unit circle.


Example 1 general solution to polar equations 6 of 8 l.jpg
Example 1: General Solution to Polar Equations (6 of 8)

  • Other solutions of

    can be found by separation of variables: For r  0 and r  1,

    and after using a partial fraction expansion and some algebra,

    where c0 and t0 are arbitrary constants.

  • Note that c0 = 0 yields r = 1,  = -t + t0, as before.


Example 1 initial value problem in polar form 8 of 8 l.jpg
Example 1: Initial Value Problem in Polar Form (8 of 8)

  • The solution satisfying the initial value problem

    is given by

  • We have the following two cases:

    • If  < 1, then r  1 from the inside as t  .

    • If  > 1, then r  1 from the outside as t  .

  • See phase portrait on right.


Limit cycle l.jpg
Limit Cycle

  • In the previous example, the circle r = 1 not only corresponds to periodic solutions of the system

    but it also attracts other nonclosed trajectories that spiral toward it as t  .

  • In general, a closed trajectory in the phase plane such that other nonclosed trajectories spiral toward it, either from the inside or the outside, as t  , is called a limit cycle.


Stability of closed trajectories l.jpg
Stability of Closed Trajectories

  • If all trajectories that start near a closed trajectory spiral toward the closed trajectory as t  , both from the inside and the outside, then the limit cycle is asymptotically stable.

  • In this case, since the closed trajectory is itself a periodic orbit rather than an equilibrium point, this type of stability is often called orbital stability.

  • If the trajectories on one side spiral toward a closed trajectory , while those on the other side spiral away as t  , then the closed trajectory is semistable.

  • If the trajectories on both sides of a closed trajectory spiral away as t  , then the closed trajectory is unstable.

  • Closed trajectories for which other trajectories neither approach nor depart from are called stable.


Theorem 9 7 1 l.jpg
Theorem 9.7.1

  • Consider the autonomous system

  • Let F and G have continuous first partial derivatives in a domain D in the xy-plane.

  • A closed trajectory of the system must necessarily enclose at least one critical (equilibrium) point.

  • If encloses only one critical point, the critical point cannot be a saddle point.

  • Note: It follows that in any region not containing a critical point, there cannot be a closed trajectory within that region.


Theorem 9 7 2 l.jpg
Theorem 9.7.2

  • Consider the autonomous system

  • Let F and G have continuous first partial derivatives in a simply connected domain D in the xy-plane.

  • If Fx + Gy has the same sign throughout D, then there is no closed trajectory of the system lying entirely within D.

  • Note: A simply connected domain in the xy-plane is a domain with no holes.

  • Also, If Fx + Gy changes sign in D, then no conclusion can be drawn.


Example 2 applying theorem 9 7 2 1 of 2 l.jpg
Example 2: Applying Theorem 9.7.2 (1 of 2)

  • Consider again the nonlinear autonomous system

  • Then

  • Thus Fx + Gy > 0 on 0  r < (1/2)½, so there is no closed trajectory in this simply connected circular disk.

  • From Example 1, there is no closed trajectory in r < 1.

  • Thus the information given in Theorem 9.7.2 may not be the best possible result.


Example 2 annular region and theorem 9 7 2 2 of 2 l.jpg
Example 2: Annular Region and Theorem 9.7.2 (2 of 2)

  • Note that

  • However, Theorem 9.7.2 does not apply since the annular region r > (1/2)½ is not simply connected.

  • Thus we cannot use Theorem 9.7.2 to conclude that there is no closed trajectory lying entirely within r > (1/2)½.

  • In fact, from Example 1, we know that r = 1 is a closed trajectory for the system that lies entirely within r > (1/2)½.


Theorem 9 7 3 poincar bendixson l.jpg
Theorem 9.7.3 (Poincaré-Bendixson)

  • Consider the autonomous system

  • Let F and G have continuous first partial derivatives in a domain D in the xy-plane.

  • Let D1 be a bounded subdomain in D, and let R be the region that consists of D1 plus its boundary (all points of R are in D).

  • Suppose that R contains no critical point of the system.

  • If there exists a constant t0 such that x = (t), y =  (t) is a solution of the system that exists and stays in R for all t > t0, then x = (t), y =  (t) either is a periodic solution (closed trajectory) or spirals toward a closed trajectory as t  .

  • In either case, the system has a periodic solution in R.


Example 3 applying theorem 9 7 3 l.jpg
Example 3: Applying Theorem 9.7.3

  • Consider again the nonlinear autonomous system

  • Since the origin is a critical point, it must be excluded from R.

  • Consider the region R defined by 0.5  r  2.

  • Recall from Example 1 that dr/dt = r(1-r) for 0.5  r  2.

  • For r = 0.5, dr/dt > 0 and hence r increases, while for r = 2, dr/dt < 0 and hence r decreases.

  • Thus a trajectory that crosses the boundary of R is entering R.

  • Consequently, any solution that starts in Rat t = t0 cannot leave but must stay in R for all t > t0, and is either a periodic solution orapproaches one as t  .


Example 4 van der pol equation 1 of 13 l.jpg
Example 4: Van der Pol Equation (1 of 13)

  • The van der Pol equation describes the current u in a triode oscillator:

  • If  = 0, then the equation reduces to u''+ u = 0, whose solutions are sine or cosine waves of period 2.

  • If  > 0, then -(1– u2) is the resistance coefficient.

  • For large , the resistance term is positive and acts to reduce the amplitude of the response.

  • For small , the resistance term is negative and causes the response to grow.

  • This suggests that perhaps there is a solution of intermediate size that other solutions approach as t increases.


Example 4 unstable critical point 2 of 13 l.jpg
Example 4: Unstable Critical Point (2 of 13)

  • Let x = u and y = u'.Then the van der Pol equation

    becomes

  • The only critical point is the origin. This system is almost linear, with linear approximation

    whose eigenvalues are [  (2 – 4)½]/2.

  • Thus the origin is an unstable spiral point for 0 <  < 2, and an unstable node for   2. In all cases, a solution that starts near the origin grows as t increases.


Example 4 theorems 9 7 1 and 9 7 2 3 of 13 l.jpg
Example 4: Theorems 9.7.1 and 9.7.2 (3 of 13)

  • With regard to periodic solutions, Theorems 9.7.1 and 9.7.2 provide only partial information.

  • From Theorem 9.7.1 we conclude that if there are closed trajectories, then they must enclose the origin.

  • To apply Theorem 9.7.2, we first calculate

  • It follows that closed trajectories, if there are any, are not contained in the strip |x| < 1, where Fx + Gy > 0.

  • To apply Theorem 9.7.3, we introduce polar coordinates to obtain the following equation for r:


Example 4 theorems 9 7 1 and 9 7 2 4 of 13 l.jpg
Example 4: Theorems 9.7.1 and 9.7.2 (4 of 13)

  • We have the following equation for r:

  • Consider the annular region R given by r1  r  r2, where r1 is small and r2 is large.

  • When r = r1, the linear term in the equation for r' dominates, and r' > 0 except on the x-axis, where sin = 0, hence r' = 0.

  • Thus the trajectories are entering R at every point on the circle r = r1, except possibly those on the x-axis, where trajectories are tangent to the circle.


Example 4 theorem 9 7 3 5 of 13 l.jpg
Example 4: Theorem 9.7.3 (5 of 13)

  • We have the following equation for r:

    and R given by r1  r  r2, where r1 is small and r2 is large.

  • When r = r2, the cubic term in the equation for r' dominates, and r' < 0 except on the x-axis, where r' = 0, and for points near the y-axis where r2cos2 < 1, and hence r' > 0.

  • Thus no matter how large a circle is chosen, there will be points on it (namely, the points on or near the y-axis) where trajectories are leaving R.

  • Therefore Theorem 9.7.3 is not applicable unless we consider more complicated regions.

  • It is possible to show that this system does have a unique limit cycle, but we will not pursue that here.


Example 4 numerical solutions 6 of 13 l.jpg
Example 4: Numerical Solutions (6 of 13)

  • We next plot numerically computed solutions.

  • Experimental observations show that the van der Pol equation has an asymptotically stable periodic solution whose period and amplitude depend on the parameter .

  • Graphs of trajectories in the phase plane and of u versus t can provide some understanding of periodic behavior.


Example 4 phase portrait 0 2 7 of 13 l.jpg
Example 4: Phase Portrait ( = 0.2)(7 of 13)

  • The graph below shows two trajectories when  = 0.2.

  • The trajectory starting near the origin spirals outward in the clockwise direction. This is consistent with the behavior of the linear approximation near the origin.

  • The other trajectory passes through (-3, 2) and spirals inward, again in the clockwise direction.

  • Both trajectories approach a closed curve that corresponds to a stable periodic solution.


Example 4 limit cycle 0 2 8 of 13 l.jpg
Example 4: Limit Cycle ( = 0.2) (8 of 13)

  • Given below are the graphs for the two trajectories previously mentioned, along with corresponding graphs of u versus t.

  • The solution solution that is initially smaller gradually increases in amplitude, while larger solution gradually decays.

  • Both solutions approach a stable periodic motion that corresponds to the limit cycle.


Example 4 phase difference 0 2 9 of 13 l.jpg
Example 4: Phase Difference ( = 0.2) (9 of 13)

  • Given below are the graphs for the two trajectories previously mentioned, along with corresponding graphs of u versus t.

  • The graph of u versus t shows that there is a phase difference between the two solutions as they approach the limit cycle.

  • The plots of u versus t are nearly sinusoidal in shape, consistent with the nearly circular limit cycle in this case.


Example 4 solution graphs 1 10 of 13 l.jpg
Example 4: Solution Graphs ( = 1)(10 of 13)

  • The graphs below show similar plots for the case  = 1.

  • Trajectories again move clockwise in the phase plane, but the limit cycle is considerably different from a circle.

  • The graphs of u versus t tend more rapidly to the limiting oscillation than before, and again show a phase difference.

  • The oscillations are somewhat less symmetric in this case, rising somewhat more steeply than the fall.


Example 4 phase portrait 5 11 of 13 l.jpg
Example 4: Phase Portrait ( = 5)(11 of 13)

  • The graph below shows a phase portrait for the case  = 5.

  • Trajectories again move clockwise in the phase plane.

  • Although solution starts far from the limit cycle, the limiting oscillation is virtually reached in a fraction of the period.

  • Starting from one of its extreme values on the x axis, the solution moves toward other extreme slowly at first, but once a certain point is reached, the rest of the transition is completed swiftly. The process is repeated in the opposite direction.


Example 4 solution graphs 5 12 of 13 l.jpg
Example 4: Solution Graphs ( = 5)(12 of 13)

  • Given below is a graph of u versus t for the case  = 5, along with the phase portrait discussed on the previous slide.

  • Note that the waveform of the limit cycle is quite different from a sine wave.


Example 4 discussion 13 of 13 l.jpg
Example 4: Discussion(13 of 13)

  • Recall that the van der Pol equation is

  • The graphs on the previous slides show that, in the absence of external excitation, the van der Pol oscillator has a certain characteristic mode of vibration for each value of .

  • The graphs of u versus t show that the amplitude of oscillator changes very little with , but period increases as  increases.

  • At the same time, the waveform changes from one that is nearly sinusoidal to one that is much less smooth.

  • The presence of a single periodic motion that attracts all nearby solutions (asymptotically stable limit cycle), is one of the characteristics associated with nonlinear equations.