Periodic orbit
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| Jeff Moehlis et al. (2006), Scholarpedia, 1(7):1358. | revision #38848 [link to/cite this article] | |||||||||||||||||||
(Redirected from Poincare-Bendixson theorem)
Curator: Dr. Jeff Moehlis, University of California, Santa Barbara, California
Curator: Dr. Kresimir Josic, University of Houston, Houston, Texas
Curator: Dr. Eric T. Shea-Brown, Courant Institute, New York University
A periodic orbit corresponds to a special type of solution for a dynamical system, namely one which repeats itself in time. A dynamical system exhibiting a stable periodic orbit is often called an oscillator.
Contents |
Definition
Periodic Orbit for a Vector Field
Consider a system of ordinary differential equations
or
corresponding to an autonomous or non-autonomous vector field, respectively.
A non-constant solution to such a system,
, is periodic if there exists a constant
such that
for all
. The period of this solution is defined to be the minimum such
. The image of the
periodicity interval
under
in the state space
is called the
periodic orbit or cycle.
Limit Cycle
A periodic orbit
on a plane (or on a two-dimensional manifold)
is called a limit cycle if it is the
-limit set or
-limit set of some point
not on the periodic orbit, that is, the set of accumulation points of either the forward or backward trajectory through
, respectively, is exactly
. Asymptotically stable and unstable periodic orbits are examples of limit cycles.
Example (Guckenheimer and Holmes, 1983; Strogatz 1994)
The figure shows the periodic orbit which exists for the vector field
where
is a parameter. Transforming to radial
coordinates, we see that the periodic orbit lies on a circle with
unit radius for any
:
This periodic orbit is a stable limit cycle for
and unstable limit cycle for
. When
, the system above has infinite number of periodic orbits and no limit cycles.
Periodic Orbit for a Map
A periodic orbit with period
for a map
is the set of
distinct points
with
(Guckenheimer and Holmes, 1983). Here
represents the composition of
with itself
times.
The smallest positive value of
for which this equality holds
is the period of the orbit. An example of a periodic orbit for a map is shown
in the figure.
Existence (or Non-Existence) of Periodic Orbits
It is sometimes possible to prove analytically that a periodic orbit exists or cannot exist for a dynamical system using the following techniques. Several of these apply for an autonomous planar vector field
Index Theory
For an autonomous planar vector field, index theory can be used to show that (Guckenheimer and Holmes, 1983):
Inside the region enclosed by a periodic orbit there must be at
least one equilibrium, i.e., a point where
.
If there is only one, it must be a
sink, source, or center. If all equilibria
inside the periodic orbit are hyperbolic, then there must be
an odd number
, of which
are saddles and
are sinks or sources.
This can be useful for showing that a periodic orbit does not exist in a region of phase space: if the appropriate equilibria are not present, a periodic orbit cannot exist.
Dulac's Criterion
For an autonomous planar vector field, Dulac's criterion states (Guckenheimer and Holmes, 1983):
Let
be a scalar function defined on a simply connected region
(so that
has no holes in it). If
is not identically zero and does not change sign in
, then
there are no periodic orbits lying entirely in
.
Bendixson's Criterion
Dulac's criterion is a generalization of Bendixson's criterion, which corresponds
to
in the above result. These criteria can be useful for
showing that a periodic orbit does not exist in a region of phase space.
Poincare-Bendixson Theorem
For an autonomous planar vector field, the Poincare-Bendixson Theorem implies (Guckenheimer and Holmes, 1983):
If a trajectory enters and does not leave a closed and bounded region of
phase space which contains no equilibria, then the trajectory must
approach a periodic orbit as
.
This can sometimes be used to establish the existence of a (stable) periodic orbit for a planar vector field.
Lienard Systems
For nonlinear oscillators satisfying Lienard's equation
the existence of a unique, stable limit cycle can be established under
appropriate general hypotheses on
and
.
For example, the damping coefficient
must be
negative near the phase space origin
so
trajectories near the origin spiral outwards, and
must be
positive far away from the origin, so that trajectories far from the
origin spiral inwards. For a detailed discussion, see Jordan and Smith (1977).
Fast-Slow Planar Systems
For a fast-slow autonomous planar vector field
simple geometrical nullcline analysis can suggest the existence of a relaxation oscillation, a special type of periodic orbit (Keener and Sneyd, 1998). The Poincare-Bendixson theorem can be used to prove the existence of a periodic orbit in some cases, but this does not establish that the orbit is a relaxation oscillation. Rigorous results for relaxation oscillations are given in Grasman (1987) and Mishchenko et al. (1994); these make use of geometric singular perturbation theory and go beyond the planar case. Fast-slow systems can also have special periodic orbit solutions called canards, although these are not robust to perturbations in planar systems.
Hilbert's 16th Problem
In 1900, David Hilbert famously posed 23 problems at the International
Congress of Mathematicians in Paris. His 16th problem involves
determining the number and location of limit cycles for an
autonomous planar vector field for which both
and
are real polynomials of degree
. At present, this
problem has not been solved, but much progress has been made in the last 100+ years.
For example, it has been shown that the number of limit cycles for such a system is
finite. This and many other results are summarized in Ilyashenko (2002).
Gradient Flows
An autonomous vector field is called a gradient flow if it can be rewritten as
where the minus sign is included by convention, so that
is a Liapunov function for the system. Periodic orbits cannot exist for gradient flows (Guckenheimer and Holmes, 1983).
Averaging for Non-autonomous Vector Fields
Sometimes a non-autonomous vector field with a small parameter (including weakly nonlinear forced oscillations) can be rewritten in a form which allows the method of averaging (over time) to be applied to understand its dynamics. Most useful for the present discussion is the result that the existence of a hyperbolic equilibrium point of the resulting autonomous equations implies the existence of a periodic orbit (possibly trivial, i.e., an equilibrium point) of the original non-autonomous system, with the same stability properties as the equilibrium point (Guckenheimer and Holmes, 1983).
Finding Periodic Orbits for a Map
From our discussion above, each point
on a period-
periodic
orbit for a map is a fixed point for the map
.
Thus, one can find points on period-
periodic orbits by solving the
algebraic equation
for
.
This may locate fixed points and points on periodic orbits with
periods less than
: for example, a fixed point with
is also a solution to
for any
. Even if the points on periodic orbits cannot be
found explicitly, analytical techniques might be used to prove that they must exist.
Numerical Methods for Finding Periodic Orbits
Periodic orbits can sometimes be found for a given vector field
using numerical methods. If a periodic orbit is stable, then forward
numerical integration of a trajectory with an initial condition in the periodic
orbit's basin of attraction will converge to the periodic orbit as
. Other methods can be used to numerically
find periodic orbits even if they are unstable. For example, the problem
of finding (stable or unstable) periodic orbits for an
autonomous vector field can be reformulated so that a
variant of the Newton-Raphson algorithm can be
applied; one numerically solves
for
and
, where
is the location
of a trajectory starting at the point
after a time
(Parker and Chua, 1989). More robust numerical methods are based on a boundary value problem on the unit interval for the periodic solution
:
where
is a phase condition selecting one periodic solution among infinitely
many periodic solutions corresponding to the same periodic orbit but having different initial points
(Doedel, Keller, and Kernevez, 1991).
This BVP should then be approximated by a proper finite-dimensional discretization (e.g.,
via orthogonal collocation with piecewise-polynomial functions) and solved for
(the discretization of)
and
.
The Newton-Raphson algorithm (or other root finding methods) can be directly applied
to find points on periodic orbits for a map: one just needs to find roots of the
equation
for the period
of
interest.
Stability of a Periodic Orbit
The stability of a periodic orbit for an autonomous vector field
can be calculated by considering the Poincare map which replaces the flow
of the
-dimensional continuous vector field with an
-dimensional map (Guckenheimer and Holmes, 1983).
Specifically, an
-dimensional
surface of section
is chosen such that the flow is
always transverse to
(see figure).
Let the successive intersections in a given direction of the solution
with
be denoted by
. The
Poincare map
determines the
-th intersection of the trajectory with
from the
-th intersection. A periodic orbit of an
autonomous vector field corresponds to a fixed point
of this
Poincare map, characterized by
. The linearization of
the Poincare map about
is
If all eigenvalues of
have modulus less than unity, then
(and thus the corresponding periodic orbit) is
asymptotically stable. If any eigenvalues of
have
modulus greater than unity, then
(and thus the
corresponding periodic orbit) is unstable. The stability
properties of a periodic orbit are independent of the cross section
(Wiggins 2003). If
is stable
then it is an attractor of the Poincare map, and the
corresponding periodic orbit is an attractor of
the vector field.
Example (continued) (Guckenheimer and Holmes 1983, Strogatz 1994)
For the Example above, the radial line
given by
is a Poincare section, parameterized by
. The corresponding Poincare map
along
this section may be found by explicitly integrating the vector field:
with fixed point
corresponding the periodic orbit.
Linearizing, we find
.
So, the periodic orbit is stable for any
and is unstable for any
.
An alternative way to determine the stability of a periodic
orbit is to use Floquet theory, which involves the
time-dependent (and
-periodic) vector field linearized around
the periodic orbit. Solutions to these linearized equations are
used to define
Floquet multipliers characterizing the
growth or decay of perturbations to the periodic orbit. It can be shown that the
eigenvalues of
are equal to
of the Floquet multipliers of the periodic orbit; the
remaining Floquet multiplier is equal to unity and
corresponds to a perturbation along the periodic
orbit (Guckenheimer and Holmes, 1983). The determination of Floquet
multipliers or the eigenvalues of
typically must
be done numerically.
Given a point
on the periodic orbit
as discussed above, the eigenvalues of the matrix
can be used to partition the
-dimensional subspace
into a direct sum of subspaces
, corresponding to eigenvalues with modulus less than 1, equal to 1, and greater than 1, respectively. If sections
are chosen to vary continuously over different base points
, then concatenations of the corresponding subspaces
form vector bundles over
. Stable, center, and unstable manifolds of
can be defined as graphs over these vector bundles.
For a non-autonomous vector field
with
for some
,
the calculation of the stability properties of a periodic orbit with
period
, where
and
are integers (see Arnold tongues),
can be done by considering a stroboscopic map which takes
The stability properties follow from the eigenvalues of this map, as above.
To determine the stability properties of a periodic orbit for a
mapping
, one can exploit the fact that a point
on a
period-
periodic orbit of the map
is a fixed point of
the map
. The stability properties of this fixed point
of
are the same as the stability properties of the periodic orbit
of the map
(Guckenheimer and Holmes, 1983).
Bifurcations Involving Periodic Orbits
A bifurcation is a qualitative change in the behavior of a dynamical system as a system parameter is varied. This could involve a change in the stability properties of a periodic orbit, and/or the creation or destruction of one or more periodic orbits. Bifurcation analysis can thus provide another (analytical or numerical) method for establishing the existence or non-existence of a periodic orbit.
Among co-dimension 1 bifurcations of periodic orbits for vector fields are (Guckenheimer and Holmes, 1983; Kuznetsov, 1998):
- Andronov-Hopf bifurcation, which results in the appearance of a small-amplitude periodic orbit.
- Saddle-node bifurcation of periodic orbits, in which two periodic orbits coalesce and annihilate each other.
- Saddle-node on invariant circle bifurcation (SNIC), in which a periodic orbit appears from a homoclinic orbit to a saddle-node equilibrium (along the central manifold).
- Homoclinic bifurcations, in which periodic orbits appear from homoclinic orbits to a saddle, saddle-focus, or focus-focus equilibrium.
- Period doubling bifurcation (also known flip bifurcation), in which a periodic orbit of period
appears near a periodic orbit of period
.
- Neimark-Sacker bifurcation, in which an invariant torus appears near a periodic orbit.
- Blue-Sky Catastrophe, in which a periodic orbit of large period appears "out of a blue sky" (actually, the orbit is homoclinic to a saddle-node periodic orbit).
These bifurcations result in the appearance or disappearance of periodic orbits, depending on the direction in which the bifurcation parameter is varied. The (dis)appearing orbits may be stable or unstable, depending, among other factors, on whether the bifurcations are subcritical or supercritical.
Periodic Orbits and Chaos
As a system parameter is varied, chaos can appear via an infinite sequence of period doubling bifurcations of periodic orbits. This is known as the Feigenbaum phenomenon or the period doubling route to chaos (Ott, 1993). Moreover, a chaotic attractor typically has a dense set of unstable periodic orbits embedded within it. Suitable averages over such periodic orbits can be used to approximate descriptive quantities for chaotic attractors such as Lyapunov exponents and fractal dimensions (Chaos Focus Issue, 1992). Such periodic orbits can sometimes be stabilized (and the chaos thus suppressed) through small manipulations of a system parameter, an approach called controlling chaos (Ott 1993).
References
- Chaos Focus Issue on Periodic Orbit Theory (1992) Chaos 2:1-158.
- E. Doedel, H.B. Keller, and J.-P. Kernevez (1991) International Journal of Bifurcation and Chaos, 1:745-772.
- J. Grasman (1987) Asymptotic Methods for Relaxation Oscillations and Applications. Springer-Verlag, New York.
- J. Guckenheimer and P. Holmes (1983) Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields. Springer-Verlag, New York
- Yu. Ilyashenko (2002) Centennial history of Hilbert's 16th problem. Bulletin of the American Mathematical Society, 39:301-354
- D.W. Jordan and P. Smith (1977) Nonlinear Ordinary Differential Equations. Clarendon Press, Oxford
- J. Keener and J. Sneyd (1998) Mathematical Physiology. Springer-Verlag, New York
- Yu.A. Kuznetsov (2004) Elements of Applied Bifurcation Theory, Third Edition. Springer-Verlag, New York.
- E.F. Mishchenko, Yu.S. Kolesov, A.Yu. Kolesov, and N.Kh. Rozov (1994) Asymptotic Methods in Singularly Perturbed Systems. Plenum Publishing Corporation, New York
- E. Ott (1993) Chaos in Dynamical Systems. Cambridge University Press, Cambridge
- T.S. Parker and L.O. Chua (1989) Practical Numerical Algorithms for Chaotic Systems. Springer-Verlag, New York
- S. Strogatz (1994) Nonlinear Dyanamics and Chaos. Perseus, Reading
- S. Wiggins (2003) Introduction to Applied Nonlinear Dynamical Systems and Chaos. Springer-Verlag, New York
Internal references
- Yuri A. Kuznetsov (2006) Andronov-Hopf bifurcation. Scholarpedia, 1(10):1858.
- John W. Milnor (2006) Attractor. Scholarpedia, 1(11):1815.
- Jan A. Sanders (2006) Averaging. Scholarpedia, 1(11):1760.
- Edward Ott (2006) Basin of attraction. Scholarpedia, 1(8):1701.
- Edward Ott (2006) Controlling chaos. Scholarpedia, 1(8):1699.
- Kresimir Josic, Eric T. Shea-Brown, Jeff Moehlis (2006) Isochron. Scholarpedia, 1(8):1361.
- Carmen C. Canavier (2006) Phase response curve. Scholarpedia, 1(12):1332.
- Yuri A. Kuznetsov (2006) Saddle-node bifurcation. Scholarpedia, 1(10):1859.
- Philip Holmes and Eric T. Shea-Brown (2006) Stability. Scholarpedia, 1(10):1838.
External Links
See also
Attractor, Bifurcations, Canards, Chaos, Dynamical Systems, Equilibrium, Fixed Point, Isochron, Phase Model, Phase Response Curve, Relaxation Oscillator, Quasiperiodicity, Stability, Unstable Periodic Orbits, Weakly Coupled Oscillators
| Jeff Moehlis, Kresimir Josic, Eric T. Shea-Brown (2006) Periodic orbit. Scholarpedia, 1(7):1358, (go to the first approved version) Created: 8 March 2006, reviewed: 24 July 2006, accepted: 25 July 2006 |






