Skip to main content
Log in

Design of coupled Andronov–Hopf oscillators with desired strange attractors

  • Original paper
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

This paper develops a design method for the interconnections of a network of Andronov–Hopf oscillators such that the system exhibits a desired strange attractor. Because of the structure of the oscillators, the desired behavior can be achieved via weak linear coupling, which destabilizes the oscillators’ phase difference. First, a set of sufficient conditions are established that result in phase destabilization, and thus instability, of a desired periodic solution. Then, an additional condition is determined to ensure that all harmonic periodic orbits will be unstable. Finally, additional numerical properties are assessed, where tuning of a small parameter can result in chaos.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Stergiou, N., Decker, L.M.: Human movement variability, nonlinear dynamics, and pathology: Is there a connection? Hum. Mov. Sci. 30(5), 869 (2011)

    Article  Google Scholar 

  2. Rabinovich, M., Abarbanel, H.: The role of chaos in neural systems. Neuroscience 87(1), 5 (1998)

    Article  Google Scholar 

  3. Buzzi, U.H., Stergiou, N., Kurz, M.J., Hageman, P.A., Heidel, J.: Nonlinear dynamics indicates aging affects variability during gait. Clin. Biomech. 18(5), 435 (2003)

    Article  Google Scholar 

  4. Cignetti, F., Schena, F., Rouard, A.: Effects of fatigue on inter-cycle variability in cross-country skiing. J. Biomech. 42(10), 1452 (2009)

    Article  Google Scholar 

  5. Kurz, M.J., Stergiou, N.: An artificial neural network that utilizes hip joint actuations to control bifurcations and chaos in a passive dynamic bipedal walking model. Biol. Cybern. 93(3), 213 (2005)

    Article  Google Scholar 

  6. Mandell, A.J., Selz, K.A.: Brain stem neuronal noise and neocortical “resonance”. J. Stat. Phys. 70(1–2), 355 (1993)

    Article  Google Scholar 

  7. Shinbrot, T., Grebogi, C., Yorke, J.A., Ott, E.: Using small perturbations to control chaos. Nature 363(6428), 411 (1993)

    Article  Google Scholar 

  8. Chen, G., Lai, D.: Anticontrol of chaos via feedback. In: Proceedings of the 36th IEEE Conference on Decision and Control, 1997, vol. 1, pp. 367–372. IEEE (1997)

  9. Chen, G., Lai, D.: Feedback anticontrol of discrete chaos. Int. J. Bifurc. Chaos 8(07), 1585 (1998)

    Article  MathSciNet  Google Scholar 

  10. Yang, L., Liu, Z., Chen, G.: Chaotifying a continuous-time system via impulsive input. Int. J. Bifurc. Chaos 12(05), 1121 (2002)

    Article  MathSciNet  Google Scholar 

  11. Morgül, Ö.: A model-based scheme for anticontrol of some chaotic systems. Int. J. Bifurc. Chaos 13(11), 3449 (2003)

    Article  MathSciNet  Google Scholar 

  12. Popovych, O.V., Maistrenko, Y.L., Tass, P.A.: Phase chaos in coupled oscillators. Phys. Rev. E 71(6), 065201 (2005)

    Article  MathSciNet  Google Scholar 

  13. Li, X., Chen, G.: Synchronization and desynchronization of complex dynamical networks: an engineering viewpoint. IEEE Trans. Circuits Syst. I: Fundam. Theory Appl. 50(11), 1381 (2003)

    Article  MathSciNet  Google Scholar 

  14. Kiss, I.Z., Rusin, C.G., Kori, H., Hudson, J.L.: Engineering complex dynamical structures: sequential patterns and desynchronization. Science 316(5833), 1886 (2007)

    Article  MathSciNet  Google Scholar 

  15. Wang, X.F., Chen, G., Yu, X.: Anticontrol of chaos in continuous-time systems via time-delay feedback. Chaos: Interdiscip. J. Nonlinear Sci. 10(4), 771 (2000)

    Article  MathSciNet  Google Scholar 

  16. Yu, S., Chen, G.: Anti-control of continuous-time dynamical systems. Commun. Nonlinear Sci. Numer. Simul. 17(6), 2617 (2012)

    Article  MathSciNet  Google Scholar 

  17. Kuramoto, Y.: Chemical Oscillations, Waves, and Turbulence, vol. 19. Springer, Berlin (2012)

    MATH  Google Scholar 

  18. Tukhlina, N., Rosenblum, M., Pikovsky, A., Kurths, J.: Feedback suppression of neural synchrony by vanishing stimulation. Phys. Rev. E 75(1), 011918 (2007)

    Article  MathSciNet  Google Scholar 

  19. Kohannim, S.: Optimal oscillations and chaos generation in biologically-inspired systems. Ph.D. thesis, UCLA (2016)

  20. Russell, D.A., Hanson, J.D., Ott, E.: Dimension of strange attractors. Phys. Rev. Lett. 45(14), 1175 (1980)

    Article  MathSciNet  Google Scholar 

  21. Farmer, J.D., Ott, E., Yorke, J.A.: In: The Theory of Chaotic Attractors, pp. 142–169. Springer (1983)

  22. Fradkov, A.L., Evans, R.J.: Control of chaos: methods and applications in engineering. Annu. Rev. Control 29(1), 33 (2005)

    Article  Google Scholar 

  23. Fradkov, A.L., Yakubovich, V.A.: The S-procedure and duality relations in nonconvex problems of quadratic programming. Vestn. LGU Ser. Mat. Mekh. Astron. 6, 101 (1979)

    MATH  Google Scholar 

  24. Moon, F.C.: Chaotic and Fractal Dynamics: Introduction for Applied Scientists and Engineers. Wiley, Hoboken (2008)

    Google Scholar 

  25. Hodgkin, A., Huxley, A.: A quantitative description of membrane currents and its application to conduction and excitation in nerve. J. Physiol. 117(4), 500 (1952)

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the National Science Foundation (NSF) Graduate Research Fellowship under Grant No. DGE-1144087.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Saba Kohannim.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

1.1 Proof of Lemma 1

Proof

Consider the following coordinate transformation \((q, p)\leftrightarrow (r,\theta )\), defined by

$$\begin{aligned}&q = C_\theta r, \qquad p = S_\theta r. \end{aligned}$$

With the new state variables \((r,\theta )\), system (3) with coupling (5) can be expressed as

$$\begin{aligned} \begin{bmatrix} {\dot{r}} \\ R{\dot{\theta }} \end{bmatrix} = \begin{bmatrix} I-R^2 \\ I \end{bmatrix} r + {{\varepsilon }}\begin{bmatrix} C_\theta &{} S_\theta \\ -S_\theta &{} C_\theta \end{bmatrix} H \begin{bmatrix}C_\theta \\ S_\theta \end{bmatrix} r , \end{aligned}$$
(19)

where \(R:=\text {diag}(r)\). Let x(t), \(t\ge 0\), be an arbitrary trajectory starting at a point in \({\mathbb {S}}_\delta \). Suppose x(t) hits the boundary of \({\mathbb {S}}_\delta \) at \(t=t_1 \ge 0\) for the first time. Then, there exists a subset of \({\mathbb {I}}_n\), denoted by \({\mathbb {I}}_{\mathrm{hit}}\), such that \(r_k(t_1)^2=1+\delta \) or \(r_k(t_1)^2=1-\delta \) for \(k\in {\mathbb {I}}_{\mathrm{hit}}\), while \(|r_i(t_1)^2-1|<\delta \) for \(i\in {\mathbb {I}}_n\backslash {\mathbb {I}}_{\mathrm{hit}}\). When \(r_k(t_1)^2=1+\delta \), using (19), the derivative of \(r_k(t)^2/2\) at \(t=t_1\) is given by

$$\begin{aligned}&\frac{\mathrm{d}}{\mathrm{d}t}\left( \frac{r_k^2}{2}\right) =r_k{\dot{r}}_k= (1-r_k^2)r_k^2\\&\quad +\,{\varepsilon }r_k\alpha ^{\mathsf{\mathrm{T}}}r=-\delta (1+\delta )+{\varepsilon }r_k\alpha ^{\mathsf{\mathrm{T}}}r, \end{aligned}$$

for some vector \(\alpha \in {\mathbb {R}}^n\) dependent on H and \(\theta (t_1)\). Since \(|r_k\alpha ^{\mathsf{\mathrm{T}}}r|\) is bounded by a number that depends only on H and \(\delta \), the second term can be made smaller in magnitude than the first term by a choice of \({\varepsilon }\). Thus, the derivative is negative, and \(r_k^2\) decreases from \(1+\delta \). By a similar argument, we see that the value of \(r_k^2\) increases when \(r_k(t_1)^2=1-\delta \). Hence, x cannot go across the boundary of \({\mathbb {S}}_\delta \), proving the invariance.

To show that \({\mathbb {S}}_\delta \) is locally attractive, suppose x(t) is outside, but not too far from, the boundary of \({\mathbb {S}}_\delta \). That is, there exist \(\rho \in {\mathbb {R}}\) and a subset of \({\mathbb {I}}_n\), denoted by \({\mathbb {I}}_{\mathrm{out}}\), such that \(\delta \le |r_k(t)^2-1|<\rho <1/2\) for \(k\in {\mathbb {I}}_{\mathrm{out}}\). The derivative of \(r_k(t)^2/2\) is then bounded by

$$\begin{aligned} \begin{array}{lll} (\mathrm{d}/\mathrm{d}t)(r_k^2/2) \le -\delta (1+\delta )+{\varepsilon }r_k\alpha ^{\mathsf{\mathrm{T}}}r &{} \text{ if } &{} 1+\delta \le r_k(t)^2<1+\rho , \\ (\mathrm{d}/\mathrm{d}t)(r_k^2/2) \ge ~~\delta (1-\delta )+{\varepsilon }r_k\alpha ^{\mathsf{\mathrm{T}}}r &{} \text{ if } &{} 1-\rho < r_k(t)^2 \le 1-\delta . \end{array} \end{aligned}$$

Following a similar argument as before, for a small enough choice of \({\varepsilon }\), the bound on the derivative is sign definite until \(r_k(t)\) hits the boundary of \({\mathbb {S}}_\delta \) to take value \(1+\delta \) or \(1-\delta \). Thus, x will enter \({\mathbb {S}}_\delta \). \(\square \)

1.2 Proof of Lemma 2

Proof

First, note from (8) that

$$\begin{aligned} \lambda = \sup {\mu } \qquad \text {such that} \qquad \lim \limits _{t\rightarrow \infty } e^{-{ 2}\mu t}||\varPhi (t)||{^2} \rightarrow \infty . \end{aligned}$$

Based on matrix norm properties, the following inequalities hold:

$$\begin{aligned} ||\varPhi (t)||{^2}\ge & {} \dfrac{1}{{2n}}||\varPhi (t)||_F^2\\\ge & {} \dfrac{1}{2n{\Vert P(t)\Vert }}\mathrm{tr}\left( \varPhi (t)^{\mathsf{\mathrm{T}}}P(t)\varPhi (t)\right) \\\ge & {} \dfrac{{ \varsigma }}{{ 2n}}\rho (t), \end{aligned}$$

where \(\Vert \cdot \Vert _F\) is the Frobenius norm, and \(\varsigma \) is a constant defined such that \(||P(t)||<1/\varsigma \) for all \(t\ge 0\). Let \(\tilde{\mu }_\delta \triangleq \tilde{\mu }-\delta \) for sufficiently small \(\delta >0\). Then,

$$\begin{aligned} \lim _{t\rightarrow \infty }e^{-2\tilde{\mu }_\delta t}||\varPhi (t)||{^2} \ge \lim _{t\rightarrow \infty } \dfrac{\varsigma }{2n}e^{-2\tilde{\mu }_\delta t}\rho (t) \rightarrow \infty . \end{aligned}$$

Since \(\tilde{\mu }_\delta \) can make the left-hand side go to infinity, we conclude that \(\lambda \ge \tilde{\mu }\). \(\square \)

1.3 Proof of Lemma 5

Proof

By Lemma 4, all possible harmonic solutions have the form (14). Substituting \(\xi (t)\) into (3) gives

where and \(\varGamma \) denote diagonal matrices of \(\omega \) and \(\gamma \), respectively. Noting that

$$\begin{aligned} \int _0^{2\pi /\omega } \xi (t)\xi (t)^{\mathsf{\mathrm{T}}}\mathrm{d}t=\frac{1}{2} \varOmega _\varphi VV^{\mathsf{\mathrm{T}}}\varOmega _\varphi ^{\mathsf{\mathrm{T}}}, \qquad V:=\left[ \begin{array}{cc} \gamma &{} 0 \\ 0 &{} \gamma \end{array}\right] , \end{aligned}$$

we see that \(\xi (t)\) is a solution of the dynamical system if and only if

This equation is further equivalent to

where we noted that and \(\varOmega _\varphi \) commute. The structure of H in (12) implies \({{\bar{H}}}_{11}={{\bar{H}}}_{22}\) and \({{\bar{H}}}_{12}=-{{\bar{H}}}_{21}\), and hence, the second and fourth equalities are satisfied. The first equality is expressed as

$$\begin{aligned} \eta ({\varepsilon },\gamma ):=(\varGamma ^2-I)\gamma -{\varepsilon }{{\bar{H}}}_{11}\gamma =0. \end{aligned}$$

Clearly, \(\gamma _i\) satisfying this condition for a small \(|{\varepsilon }|\) has to be close to 1, \(-1\), or 0. All the harmonic solutions near can be captured by those near due to the freedom in \(\varphi \). By the implicit function theorem, \(\eta ({\varepsilon },\gamma )=0\) is solvable for \(\gamma \) when \(|{\varepsilon }|\) is sufficiently small since and hold. In particular, the solution in the neighborhood of is expressed as \(\gamma =g({\varepsilon })\) for a continuously differentiable function g such that , and the derivative is given by

The formula for \(\gamma \) now follows as the Taylor series and that for \(\omega \) is then obtained by solving the third equality. \(\square \)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kohannim, S., Iwasaki, T. Design of coupled Andronov–Hopf oscillators with desired strange attractors. Nonlinear Dyn 100, 1659–1672 (2020). https://doi.org/10.1007/s11071-020-05547-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11071-020-05547-0

Keywords

Navigation