Hopf bifurcation

In the mathematical theory of bifurcations, a Hopf bifurcation is a critical point where a system's stability switches and a periodic solution arises.^[1] More accurately, it is a local bifurcation in which a fixed point of a dynamical system loses stability, as a pair of complex conjugate eigenvalues - of the linearization around the fixed point - crosses the complex plane imaginary axis. Under reasonably generic assumptions about the dynamical system, a small-amplitude limit cycle branches from the fixed point.

A Hopf bifurcation is also known as a Poincaré–Andronov–Hopf bifurcation, named after Henri Poincaré, Eberhard Hopf, and Aleksandr Andronov.

Overview

Supercritical and subcritical Hopf bifurcations

The limit cycle is orbitally stable if a specific quantity called the first Lyapunov coefficient is negative, and the bifurcation is supercritical. Otherwise it is unstable and the bifurcation is subcritical.

The normal form of a Hopf bifurcation is:

{\frac {dz}{dt}}=z((\lambda +i)+b|z|^{2}),

where z, b are both complex and λ is a parameter.

Write: $b=\alpha +i\beta .\,$ The number α is called the first Lyapunov coefficient.

If α is negative then there is a stable limit cycle for λ > 0:

z(t)=re^{{i\omega t}}\,

where

r={\sqrt {-\lambda /\alpha }}{\text{ and }}\omega =1+\beta r^{2}.\,

The bifurcation is then called supercritical.

If α is positive then there is an unstable limit cycle for λ < 0. The bifurcation is called subcritical.

Example

The Hopf bifurcation in the Selkov system (see article). As the parameters change, a limit cycle (in blue) appears out of an unstable equilibrium.

Hopf bifurcations occur in the Lotka–Volterra model of predator–prey interaction (known as paradox of enrichment), the Hodgkin–Huxley model for nerve membrane,^[2] the Selkov model of glycolysis,^[3] the Belousov–Zhabotinsky reaction, the Lorenz attractor and in the following simpler chemical system called the Brusselator as the parameter B changes:

{\frac {dX}{dt}}=A+X^{2}Y-(B+1)X

{\frac {dY}{dt}}=BX-X^{2}Y.

The Selkov model is

{\frac {dx}{dt}}=-x+ay+x^{2}y,~~{\frac {dy}{dt}}=b-ay-x^{2}y.

The phase portrait illustrating the Hopf bifurcation in the Selkov model is shown on the right.^[4]

In railway vehicle systems, Hopf bifurcation analysis is notably important. Conventionally a railway vehicle has stable motion in low speeds, when it reaches to high speeds stability changes to unstable form. The main purpose of nonlinear analysis of rail vehicle system dynamics is to show the view of analytical investigation of bifurcation, nonlinear lateral stability and hunting behavior of rail vehicles in a tangent track. This study contains Bogoliubov method for the analysis.^[5]

Definition of a Hopf bifurcation

The appearance or the disappearance of a periodic orbit through a local change in the stability properties of a steady point is known as the Hopf bifurcation. The following theorem works with steady points with one pair of conjugate nonzero purely imaginary eigenvalues. It tells the conditions under which this bifurcation phenomenon occurs.

Theorem (see section 11.2 of ^[6]). Let $J_{0}$ be the Jacobian of a continuous parametric dynamical system evaluated at a steady point $Z_{e}$ of it. Suppose that all eigenvalues of $J_{0}$ have negative real parts except one conjugate nonzero purely imaginary pair $\pm i\beta$ . A Hopf bifurcation arises when these two eigenvalues cross the imaginary axis because of a variation of the system parameters.

Routh–Hurwitz criterion

Routh–Hurwitz criterion (section I.13 of ^[7]) gives necessary conditions so that a Hopf bifurcation occurs. Let us see how one can use concretely this idea.^[8]

Sturm series

Let $p_{0},p_{1},\dots ,p_{k}$ be Sturm series associated to a characteristic polynomial $P$ . They can be written in the form:

p_{i}(\mu )=c_{{i,0}}\mu ^{{k-i}}+c_{{i,1}}\mu ^{{k-i-2}}+c_{{i,2}}\mu ^{{k-i-4}}+\cdots

The coefficients $c_{{i,0}}$ for $i$ in $\{1,\dots ,k\}$ correspond to what is called Hurwitz determinants.^[8] Their definition is related to the associated Hurwitz matrix.

Propositions

Proposition 1. If all the Hurwitz determinants $c_{{i,0}}$ are positive, apart perhaps $c_{{k,0}}$ then the associated Jacobian has no pure imaginary eigenvalues.

Proposition 2. If all Hurwitz determinants $c_{{i,0}}$ (for all $i$ in $\{0,\dots ,k-2\}$ are positive, $c_{{k-1,0}}=0$ and $c_{{k-2,1}}<0$ then all the eigenvalues of the associated Jacobian have negative real parts except a purely imaginary conjugate pair.

The conditions that we are looking for so that a Hopf bifurcation occurs (see theorem above) for a parametric continuous dynamical system are given by this last proposition.

Example

Let us consider the classical Van der Pol oscillator written with ordinary differential equations:

\left\{{\begin{array}{l}{\dfrac {dx}{dt}}=\mu (1-y^{2})x-y,\\{\dfrac {dy}{dt}}=x.\end{array}}\right.

The Jacobian matrix associated to this system follows:

J={\begin{pmatrix}-\mu (-1+y^{2})&-2\mu yx-1\\1&0\end{pmatrix}}.

The characteristic polynomial (in $\lambda$ ) of the linearization at (0,0) is equal to:

P(\lambda )=\lambda ^{2}-\mu \lambda +1.

The coefficients are: $a_{0}=1,a_{1}=-\mu ,a_{2}=1$
The associated Sturm series is:

{\begin{array}{l}p_{0}(\lambda )=a_{0}\lambda ^{2}-a_{2}\\p_{1}(\lambda )=a_{1}\lambda \end{array}}

The Sturm polynomials can be written as (here $i=0,1$ ):

p_{i}(\mu )=c_{{i,0}}\mu ^{{k-i}}+c_{{i,1}}\mu ^{{k-i-2}}+c_{{i,2}}\mu ^{{k-i-4}}+\cdots

The above proposition 2 tells that one must have:

c_{{0,0}}=1>0,c_{{1,0}}=-\mu =0,c_{{0,1}}=-1<0.

Because 1 > 0 and −1 < 0 are obvious, one can conclude that a Hopf bifurcation may occur for Van der Pol oscillator if $\mu =0$ .

References

↑ "Hopf Bifurcations" (PDF). MIT.
↑ Guckenheimer, J.; Labouriau, J.S. (1993), "Bifurcation of the Hodgkin and Huxley equations: A new twist", Bulletin of Mathematical Biology, 55 (5): 937–952, doi:10.1007/BF02460693 .
↑ "Selkov Model Wolfram Demo". [demonstrations.wolfram.com ]. Retrieved 30 September 2012.
↑ For detailed derivation, see Strogatz, Steven H. (1994). Nonlinear Dynamics and Chaos. Addison Wesley. p. 205. ISBN 0-7382-0453-6.
↑ Serajian, Reza (2011). "Effects of the bogie and body inertia on the nonlinear wheel-set hunting recognized by the hopf bifurcation theory". International Journal of Automative Engineering. 3 (4): 186&ndash, 196.
↑ Hale, J.; Koçak, H. (1991). Dynamics and Bifurcations. Texts in Applied Mathematics. 3. Berlin: Springer-Verlag. ISBN 3-540-97141-6.
↑ Hairer, E.; Norsett, S. P.; Wanner, G. (1993). Solving Ordinary Differential Equations I: Nonstiff Problems (Second ed.). New York: Springer-Verlag. ISBN 3-540-56670-8.
1 2 Kahoui, M. E.; Weber, A. (2000). "Deciding Hopf bifurcations by quantifier elimination in a software component architecture". Journal of Symbolic Computation. 30 (2): 161&ndash, 179. doi:10.1006/jsco.1999.0353.

External links

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[1] "Hopf Bifurcations" (PDF). MIT.

[2] Guckenheimer, J.; Labouriau, J.S. (1993), "Bifurcation of the Hodgkin and Huxley equations: A new twist", Bulletin of Mathematical Biology, 55 (5): 937–952, doi:10.1007/BF02460693 .

[Selkov_Model-3] "Selkov Model Wolfram Demo". [demonstrations.wolfram.com ]. Retrieved 30 September 2012.

[Strogatz1994-4] For detailed derivation, see Strogatz, Steven H. (1994). Nonlinear Dynamics and Chaos. Addison Wesley. p. 205. ISBN 0-7382-0453-6.

[Reza_Serajian-5] Serajian, Reza (2011). "Effects of the bogie and body inertia on the nonlinear wheel-set hunting recognized by the hopf bifurcation theory". International Journal of Automative Engineering. 3 (4): 186&ndash, 196.

[HaleKocak1991-6] Hale, J.; Koçak, H. (1991). Dynamics and Bifurcations. Texts in Applied Mathematics. 3. Berlin: Springer-Verlag. ISBN 3-540-97141-6.

[HairerNorsettWanner1993-7] Hairer, E.; Norsett, S. P.; Wanner, G. (1993). Solving Ordinary Differential Equations I: Nonstiff Problems (Second ed.). New York: Springer-Verlag. ISBN 3-540-56670-8.

[KahouiWeber2000-8] 1 2 Kahoui, M. E.; Weber, A. (2000). "Deciding Hopf bifurcations by quantifier elimination in a software component architecture". Journal of Symbolic Computation. 30 (2): 161&ndash, 179. doi:10.1006/jsco.1999.0353.

Hopf bifurcation

Overview

Supercritical and subcritical Hopf bifurcations

Example

Definition of a Hopf bifurcation

Routh–Hurwitz criterion

Sturm series

Propositions

Example

See also

References

Further reading

External links