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Contemporary Engineering , Vol. 11, 2018, no. 85, 4245 - 4252 HIKARI Ltd, www.m-hikari.com https://doi.org/10.12988/ces.2018.88389

Bifurcation Analysis of the Van der Pol Oscillator

Diana Marcela Devia Narvaez

Department of Mathematics and GIMAE Universidad Tecnol´ogicade Pereira Pereira, Colombia

Germ´anCorrea V´elez

Department of Mathematics and GIMAE Universidad Tecnol´ogicade Pereira Pereira, Colombia

Diego Fernando Devia Narvaez

Department of Mathematics and GREDYA Universidad Tecnol´ogicade Pereira Pereira, Colombia

Copyright c 2018 Diana Marcela Devia Narvaez et al. This article is distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In the present paper a detailed analysis of the bifurcation of the Van der Pol oscillator is carried out, which starts by giving an account of the theory of chaos and dynamic systems, complements mentioning the main theoretical concepts of the dynamic systems and the different forms of analysis that exist, then continues to expose the discovery of the Van der Pol oscillator, to finally expose the results obtained from the bifurcation analysis of the oscillator.

Keywords: Bifurcation, Van Der Pol oscillator, chaos 4246 Diana Marcela Devia Narvaez et al.

1 Introduction

Chaos theory is a relatively new branch of mathematics, with characteristics that distinguish it from other disciplines. In general, the concept of chaos arises from the study of dynamic systems, especially non-linear systems. Therefore, chaotic behavior can be found in any area of from medicine to ecology. The study of this theory has generated new techniques of analysis and study methods for the characterization of dynamic systems, in addition to the fact that the development of technology and simulation capacity that has been cur- rently has revolutionized this discipline. [1]

When we refer naturally to chaotic systems, we refer to phenomena with irregular dynamics, of a random nature or unpredictable at any moment of time. For these systems, physical theories are ineffective and that is why they are often relegated, without paying much attention to them. However, the theory of chaos has modified this thinking, highlighting the importance of the analysis of non-linear systems. An example of nonlinearity is the Van der Pol oscillator which was described by the engineer and physicist Balthasar Van der Pol, while examining the dynamics of an electrical circuit. [2]

2 Van del Pol Oscillator

The van oscillator of the Pol is described by a second-order differential equa- tion, where x is the position as a of time and µ is the scalar parameter that dominates non-linearity and .

x¨ − µ 1 − x2 x˙ + x = 0 (1) This system was described by the engineer and physicist Balthasar Van der Pol, who found stable , which are known as limit cycles, while working investigating the behavior of circuits. It used vacuum valves and contained other common elements of electrical circuits. This system was one of the first experimental discoveries of and after this it has had a long history in the modeling of physical systems of different areas of science, such as: , geology, neurology, among others. [3] The electrical circuit described by Eq.(1) contains active elements such as the non-linear current source, described by:

i = φ (v) = γv3 − αv, (2) where i and v are current and electrical voltage respectively. The system that describes the circuit shown in Figure 1 is: Bifurcation analysis of the Van der Pol oscillator 4247

Figure 1: Electric circuit of the Van der Pol oscillator.

1 V˙ = (−φ (V ) − W ) C (3) 1 W˙ = V, L which can be written as 1 1 V¨ − α − 3γV 2 V˙ + V = 0 (4) C LC Subsequently, the parameters of the electric circuit are condensed in what was initially proposed in the model (1), leaving the µ parameter that controls the non-linearity of the system and as it will be seen later, it controls the stability of the system. [4,5]

2.1 Bifurcations in the Van der Pol oscillator To begin the analysis, first the order of the Eq.(1) is reduced and the following is proposed: x˙ = y (5) y˙ = µ 1 − x2 y − x Now, to find the equilibrium points of the system analytically, the velocity vector is equal to zero, and subsequently the values that take x and y are taken. (x, ˙ y˙) = (0, 0) → (x∗, y∗) = (0, 0)

2.2 Linearization of the system We consider the system x˙ = f(x, y) y˙ = g(x, y) 4248 Diana Marcela Devia Narvaez et al. and assuming that (x∗, y∗) is a fixed point, we have

u = x − x∗, v = y − y∗

Now, using Taylor series we get df df u˙ = u + v + O(u2, v2, uv) dx dy dg dg v˙ = u + v + O(u2, v2, uv), dx dy where the O(u2, v2, uv) function represents the quadratic terms, which are disregarded and the Jacobian matrix of the system is obtained, which must be evaluated in the fixed point, found previously, in this way the linearized system is obtained: ! u˙ df df u = dx dy (6) v˙ dg dg v dx dy (x∗,y∗) As it could be observed in the phase plane [6], and by simple inspection in the system (5) the fixed point is (x∗, y∗) = (0, 0), with the evaluation of these points in the Jacobian system Linearization is obtained:

u˙  0 1  u = −2µxy − 1 −µ(x2 − 1) v˙ (0,0) v

u˙  0 1 u = v˙ −1 µ v After obtaining the linearization of the system it is possible to notice that the Jacobian contains the µ parameter of the system, so the eigenvalues of the system and its stability will be determined by the value of the parameter.

The characteristic polynomial obtained from the system is:

λ2 − µλ + 1, and the eigenvalues are determined by the following equations:

µ + pµ2 − 4 µ − pµ2 − 4 λ = , λ = 1 2 2 2 It is possible to notice that solutions are obtained in conjugate pairs for values of −2 < µ < 2, even so, it is not clear if fork point bifurcations are generated. Figure 2 shows more clearly the variation in real scale of the eigenvalues with respect to the parameter µ. [7] Bifurcation analysis of the Van der Pol oscillator 4249

Figure 2: Eigenvalues dependent of µ.

Figure 3: Phase diagram for µ = −3.

3 Obtaining limit cycles

Parallel to the system stability analysis performed previously, it must be known if the system has limit cycles. Analytically, it can be concluded that there is a in the system if it meets the conditions of the Li´enardsystems. From the Van der Pol system analogous to the Li´enardsystems, we have:

f(x) = µ(x2 − 1), g(x) = x

According to the Li´enardtheorem, the function f is continuously differentiable provided that µ ≥ 0. Therefore, it is correct to conclude that the Van der Pol system is a Li´enardtype system, with a single limit cycle that surrounds the origin (equilibrium point). However, if µ < 0, the Van der Pol oscillator ceases to be a Lienard type system because f(x) would not meet the conditions of 4250 Diana Marcela Devia Narvaez et al.

Figure 4: Phase diagram for µ = −0.5.

Figure 5: .

the theorem. To complement the conclusions obtained in an analytical way, the phase diagrams obtained in numerical form for different values of the bi- furcation parameter are also included (see Figures 3,4,5).

From the previous results obtained analytically and graphically, it is con- cluded that a bifurcation occurs at the equilibrium point (x∗, y∗) = (0, 0) when µ = 0. You can also observe the correlation of graphical results with the vari- ation of the values of µ, it is furthermore that when the equilibrium point is stable (µ < 0) the system has an unstable limit cycle and when the equilibrium point is unstable (µ > 0) you have a stable limit cycle, in other words when the equilibrium point repels the trajectories the limit cycle will attract them, you do not have the same deduction for when µ = 0, in this case you will have Bifurcation analysis of the Van der Pol oscillator 4251 a center with the trajectories in a clockwise direction.

4 Conclusion

The qualitative analysis of dynamic systems provides relevant information about their stability and behavior in the face of changes in the parameters that dominate them, in this document the Van der Pol oscillator behavior and the bifurcation that occurs in the before the variation of the parameter µ. The analysis presented here is very useful for future investigations concerning the second order systems, besides giving a guide for the realization of the qualita- tive analysis, it provides relevant information for the analysis of Lienard type systems. It is of great interest the bifurcation that occurs when the µ parame- ter takes the value of zero, since when it takes positive values (the equilibrium point is stable) it is possible to find a stable limit cycle as a result of the Van der Pol system acquires the form of a Lienard system, however, when the µ parameter is negative (unstable fixed point) it is not possible to find the limit cycle of the system, finally the results obtained by numerical analysis confirm the existence of a stable limit cycle when µ ≥ 0 and show the existence of an unstable limit cycle when µ < 0.

Acknowledgements. We would like to thank the referee for his valuable suggestions that improved the presentation of this paper and our gratitude to the Department of Mathematics of the Universidad Tecnol´ogicade Pereira (Colombia), GEDNOL Research Group and the Grupo de Investigaci´onen Matem´aticaAplicada y Educaci´onGIMAE.

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Received: August 19, 2018; Published: September 27, 2018