Skip to main content
Log in

Nonlinear feedback anti-control of limit cycle and chaos in a mechanical oscillator: theory and experiment

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

Abstract

Though engineers believe that self-excited oscillation and chaos is detrimental, recent research has revealed that self-excited periodic and chaotic oscillation can be effectively utilized in many engineering processes and devices for significant benefits. Then a simple nonlinear acceleration feedback controller is proposed to generate self-excited periodic and chaotic oscillation in a mechanical oscillator. Analytical expressions relating the amplitude of limit cycles and control parameters are obtained by the method of multiple time scales. Analytical results are verified by numerical simulations performed in MATLAB–SIMULINK. Existence of chaotic oscillations is confirmed by numerical simulations. An extensive parametric study is carried out to reveal the nature of the chaotic oscillations and its dependence on the controller parameters. Theoretical results are finally verified by experiments. It is generally observed that the same controller can be used to induce both periodic and chaotic oscillations just by flipping the phase of the controller. This is possibly the first example where the same controller can be utilized to generate periodic and chaotic oscillation in a mechanical system. The findings of the paper are believed to be used in macro- and micro-mechanical systems.

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
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27

Similar content being viewed by others

References

  1. van der Pol, B.: LXXXVIII On “relaxation-oscillations.” Lond. Edinb. Dublin. Philos. Mag. J. Sci. 2, 978–992 (1926). https://doi.org/10.1080/14786442608564127

    Article  Google Scholar 

  2. Rayleigh, L.: XXXIII On maintained vibrations. Lond. Edinb. Dublin Philos. Mag. J. Sci. 15, 229–235 (1883). https://doi.org/10.1080/14786448308627342

    Article  MathSciNet  Google Scholar 

  3. Babitsky, V.I.: Autoresonant mechatronic systems. Mechatronics 5, 483–495 (1995). https://doi.org/10.1016/0957-4158(95)00026-2

    Article  Google Scholar 

  4. Pelgné, G., Kamnev, E., Brissaud, D., Gouskov, A.: Self-excited vibratory drilling: A dimensionless parameter approach for guiding experiments. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 219, 73–86 (2005). https://doi.org/10.1243/095440505X8118

    Article  Google Scholar 

  5. Chaodong, L., Xiaojing, H.: A bio-mimetie pipe crawling microrobot driven based on self-excited vibration. In: 2007 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 984–988 (2007). doi: https://doi.org/10.1109/ROBIO.2007.4522297

  6. Lee, Y., Lim, G., Moon, W.: A piezoelectric micro-cantilever bio-sensor using the mass-micro-balancing technique with self-excitation. Microsyst. Technol. 13, 563–567 (2007). https://doi.org/10.1007/s00542-006-0216-x

    Article  Google Scholar 

  7. Batako, A.D., Babitsky, V.I., Halliwell, N.A.: A self-excited system for percussive-rotary drilling. J. Sound Vib. 259, 97–118 (2003). https://doi.org/10.1006/jsvi.2002.5158

    Article  Google Scholar 

  8. Babitsky, V., Astashev, V.: Nonlinear dynamics and control of ultrasonically assisted machining. J. Vib. Control. 13, 441–460 (2007). https://doi.org/10.1177/1077546307074222

    Article  MATH  Google Scholar 

  9. Kwaśniewki, J., Dominik, I., Lalik, K.: Application of self-oscillating system for stress measurement in metal. J. Vibroeng. 14, 61–66 (2012)

    Google Scholar 

  10. Ono, K., Takahashi, R., Shimada, T.: Self-excited walking of a biped mechanism. Int. J. Rob. Res. 20, 953–966 (2001). https://doi.org/10.1177/02783640122068218

    Article  Google Scholar 

  11. Ono, K., Furuichi, T., Takahashi, R.: Self-excited walking of a biped mechanism with Feet. Int. J. Rob. Res. 23, 55–68 (2004). https://doi.org/10.1177/0278364904038888

    Article  Google Scholar 

  12. Luo, J., Su, Y., Ruan, L., Zhao, Y., Kim, D., Sentis, L., Fu, C.: Robust bipedal locomotion based on a hierarchical control structure. Robotica 37, 1750–1767 (2019). https://doi.org/10.1017/S0263574719000237

    Article  Google Scholar 

  13. Malas, A., Chatterjee, S.: Generating self-excited oscillation in a class of mechanical systems by relay-feedback. Nonlinear Dyn. 76, 1253–1269 (2014). https://doi.org/10.1007/s11071-013-1208-x

    Article  MathSciNet  Google Scholar 

  14. Malas, A., Chatterjee, S.: Modal self-excitation by nonlinear acceleration feedback in a class of mechanical systems. J. Sound Vib. 376, 1–17 (2016). https://doi.org/10.1016/j.jsv.2016.04.029

    Article  Google Scholar 

  15. Malas, A., Chatterjee, S.: Amplitude controlled adaptive feedback resonance in a single degree-of-freedom mass-spring mechanical system. Proc. Eng. 144, 697–704 (2016). https://doi.org/10.1016/j.proeng.2016.05.070

    Article  Google Scholar 

  16. Malas, A., Chatterjee, S.: Modeling and design of direct nonlinear velocity feedback for modal self-excitation in a class of multi degrees-of-freedom mechanical systems. JVC/J. Vib. Control. 23, 656–672 (2017). https://doi.org/10.1177/1077546315582292

    Article  MathSciNet  MATH  Google Scholar 

  17. Malas, A., Chatterjee, S.: Analysis and synthesis of modal and non-modal self-excited oscillations in a class of mechanical systems with nonlinear velocity feedback. J. Sound Vib. 334, 296–318 (2015). https://doi.org/10.1016/j.jsv.2014.09.011

    Article  Google Scholar 

  18. Aguilar, L.T., Boiko, I., Fridman, L., Iriarte, R.: Generating self-excited oscillations via two-relay controller. IEEE Trans. Automat. Contr. 54, 416–420 (2009). https://doi.org/10.1109/TAC.2008.2009615

    Article  MathSciNet  MATH  Google Scholar 

  19. Nakamura, T., Yabuno, H., Yano, M.: Amplitude control of self-excited weakly coupled cantilevers for mass sensing using nonlinear velocity feedback control. Nonlinear Dyn. 99, 85–97 (2020). https://doi.org/10.1007/s11071-019-05287-w

    Article  MATH  Google Scholar 

  20. Urasaki, S., Yabuno, H.: Identification method for backbone curve of cantilever beam using van der Pol-type self-excited oscillation. Nonlinear Dyn. (2020). https://doi.org/10.1007/s11071-020-05945-4

    Article  Google Scholar 

  21. Tanaka, Y., Kokubun, Y., Yabuno, H.: Proposition for sensorless self-excitation by a piezoelectric device. J. Sound Vib. 419, 544–557 (2018). https://doi.org/10.1016/j.jsv.2017.11.033

    Article  Google Scholar 

  22. Mouro, J., Tiribilli, B., Paoletti, P.: Nonlinear behaviour of self-excited microcantilevers in viscous fluids. J. Micromech. Microeng. 27, 095008 (2017). https://doi.org/10.1088/1361-6439/aa7a6f

    Article  Google Scholar 

  23. Yabuno, H., Higashino, K., Kuroda, M., Yamamoto, Y.: Self-excited vibrational viscometer for high-viscosity sensing. J. Appl. Phys. 116, 124305 (2014). https://doi.org/10.1063/1.4896487

    Article  Google Scholar 

  24. Endo, D., Yabuno, H., Higashino, K., Yamamoto, Y., Matsumoto, S.: Self-excited coupled-microcantilevers for mass sensing. Appl. Phys. Lett. 106, 223105 (2015). https://doi.org/10.1063/1.4921082

    Article  Google Scholar 

  25. Mouro, J., Tiribilli, B., Paoletti, P.: A versatile mass-sensing platform with tunable nonlinear self-excited microcantilevers. IEEE Trans. Nanotechnol. (2018). https://doi.org/10.1109/TNANO.2018.2829404

    Article  Google Scholar 

  26. Endo, D., Yabuno, H., Yamamoto, Y., Matsumoto, S.: Mass sensing in a liquid environment using nonlinear self-excited coupled-microcantilevers. J. Microelectromech. Syst. 27, 774–779 (2018). https://doi.org/10.1109/JMEMS.2018.2866877

    Article  Google Scholar 

  27. Lin, Y., Yabuno, H., Liu, X., Yamamoto, Y., Matsumoto, S.: Highly sensitive AFM using self-excited weakly coupled cantilevers. Appl. Phys. Lett. 115, 133105 (2019). https://doi.org/10.1063/1.5115836

    Article  Google Scholar 

  28. Lorenz, E.N.: Deterministic nonperiodic flow. J. Atmos. Sci. 20, 130–141 (1963). https://doi.org/10.1175/1520-0469(1963)020%3c0130:DNF%3e2.0.CO;2

    Article  MathSciNet  MATH  Google Scholar 

  29. Barboza, R.U.Y.: Dynamics of a hyperchaotic lorenz system. Int. J. Bifurc. Chaos 17, 4285–4294 (2007). https://doi.org/10.1142/S0218127407019950

    Article  MathSciNet  MATH  Google Scholar 

  30. Wang, X., Wang, M.: A hyperchaos generated from Lorenz system. Phys. A Stat. Mech. Appl. 387, 3751–3758 (2008). https://doi.org/10.1016/j.physa.2008.02.020

    Article  MathSciNet  Google Scholar 

  31. Wang, Bo H. (Seoul, KR), Koh, Seok B. (Seoul, KR), Ahn, Seung K. (Seoul, KR), Roychowdhury, Shounak (Seoul, K.: “Chaos washing machine and a method of washing thereof,” http://www.freepatentsonline.com/5560230.html (1996)

  32. Nomura, H., Wakami, N., Aihara, K.: Time-series analysis of behavior of a two-link nozzle in a dishwasher. Electron. Commun. Jpn. Part III Fundam. Electron. Sci. 79, 88–97 (1996). https://doi.org/10.1002/ecjc.4430790909

    Article  Google Scholar 

  33. Tani, J.: Proposal of chaotic steepest descent method for neural networks and analysis of their dynamics. Electron. Commun. Jpn. Part III Fundam. Electron. Sci. 75, 62–70 (1992). https://doi.org/10.1002/ecjc.4430750406

    Article  MathSciNet  Google Scholar 

  34. Moreno-Valenzuela, J., Torres-Torres, C.: Adaptive chaotification of robot manipulators via neural networks with experimental evaluations. Neurocomputing 182, 56–65 (2016). https://doi.org/10.1016/j.neucom.2015.11.085

    Article  Google Scholar 

  35. Miranda-Colorado, R., Aguilar, L.T., Moreno-Valenzuela, J.: A model-based velocity controller for chaotisation of flexible joint robot manipulators. Int. J. Adv. Robot. Syst. 15, 172988141880252 (2018). https://doi.org/10.1177/1729881418802528

    Article  Google Scholar 

  36. Aihara, K.: Chaos and Its Applications. Procedia IUTAM. 5, 199–203 (2012). https://doi.org/10.1016/j.piutam.2012.06.027

    Article  Google Scholar 

  37. Fortuna, L., Frasca, M., Rizzo, A.: Chaotic pulse position modulation to improve the efficiency of sonar sensors. IEEE Trans. Instrum. Meas. 52, 1809–1814 (2003). https://doi.org/10.1109/TIM.2003.820452

    Article  Google Scholar 

  38. Sahin, S., Kavur, A.E., Demiroglu Mustafov, S., Seydibeyoglu, O., Baser, O., Isler, Y., Guzelis, C.: Spatiotemporal chaotification of delta robot mixer for homogeneous graphene nanocomposite dispersing. Rob. Auton. Syst. 134, 103633 (2020). https://doi.org/10.1016/j.robot.2020.103633

    Article  Google Scholar 

  39. Brandt, M.E., Chen, G.: Bifurcation control of two nonlinear models of cardiac activity. IEEE Trans. Circuits Syst. I Fundam. Theory Appl. 44, 1031–1034 (1997). https://doi.org/10.1109/81.633897

    Article  Google Scholar 

  40. Georgiou, I.T., Schwartz, I.B.: Dynamics of large scale coupled structural/mechanical systems: a singular perturbation/proper orthogonal decomposition approach. SIAM J. Appl. Math. 59, 1178–1207 (1999). https://doi.org/10.1137/S0036139997299802

    Article  MathSciNet  MATH  Google Scholar 

  41. Gao, Y., Chau, K.T.: Chaotification of permanent-magnet synchronous motor drives using time-delay feedback. In: IECON Proceedings (Industrial Electronics Conference), pp. 762–766. IEEE (2002)

  42. Cuomo, K.M., Oppenheim, A.V.: Circuit implementation of synchronised chaos with applications to communications. Phys. Rev. Lett. 71, 65–68 (1993). https://doi.org/10.1103/PhysRevLett.71.65

    Article  Google Scholar 

  43. Fedula, M., Hovorushchenko, T., Nicheporuk, A., Martynyuk, V.: Chaos-based signal detection with discrete-time processing of the Duffing attractor. East. Eur. J. Enterp. Technol. 4, 44–51 (2019). https://doi.org/10.15587/1729-4061.2019.175787

    Article  Google Scholar 

  44. Zhou J, Xu D, Li Y: Chaotifing duffing-type system with large parameter range based on optimal time-delay feedback control. In: 2010 International workshop on chaos-fractal theories and applications, pp. 121–126. IEEE (2010)

  45. Li, Y., Xu, D., Fu, Y., Zhou, J.: Chaotification of a nonlinear vibration isolation system by dual time delayed feedback control. Int. J. Bifurc. Chaos 23, 1–20 (2013). https://doi.org/10.1142/S021812741350096X

    Article  MathSciNet  MATH  Google Scholar 

  46. Chai K., Li S., Lou J.J., Yu X., Liu Y.S., Yang C.Q.: Line spectra chaotification of the nonlinear vibration isolation system on the flexible foundation based on the open-plus-nonlinear-closed-loop method. J. Vib. Control. 107754632093376 (2020). https://doi.org/10.1177/1077546320933762

  47. Zhang, J., Tang, T., Fang, W.: Line spectrum chaotification on QZS systems with time-delay control. Complexity 2020, 1–14 (2020). https://doi.org/10.1155/2020/1932406

    Article  MATH  Google Scholar 

  48. Chen, G., Shi, Y.: Introduction to anti-control of discrete chaos: Theory and applications. Philos. Trans. R Soc. A Math. Phys. Eng. Sci. 364, 2433–2447 (2006). https://doi.org/10.1098/rsta.2006.1833

    Article  MathSciNet  MATH  Google Scholar 

  49. Chen, Q., Hong, Y., Chen, G.: Chaotic behaviors and toroidal/spherical attractors generated by discontinuous dynamics. Phys. A Stat. Mech. Appl. 371, 293–302 (2006). https://doi.org/10.1016/j.physa.2006.03.047

    Article  Google Scholar 

  50. Zhang, Y., Liu, X., Zhang, H., Jia, C.: Constructing chaotic systems from a class of switching systems. Int. J. Bifurc. Chaos 28, 1850032 (2018). https://doi.org/10.1142/S0218127418500323

    Article  MathSciNet  MATH  Google Scholar 

  51. Ueta, T., Chen, G.: Bifurcation Analysis of Chen’s equation. Int. J. Bifurc. Chaos. 10, 1917–1931 (2000). https://doi.org/10.1142/S0218127400001183

    Article  MathSciNet  MATH  Google Scholar 

  52. Kwiatkowski, R.: Dynamic analysis of double pendulum with variable mass and initial velocities. Proc. Eng. 136, 175–180 (2016). https://doi.org/10.1016/j.proeng.2016.01.193

    Article  Google Scholar 

  53. Johnson, M.A., Moon, F.C.: Experimental characterisation of quasiperiodicity and chaos in a mechanical system with delay. Int. J. Bifurc. Chaos. 09, 49–65 (1999). https://doi.org/10.1142/S0218127499000031

    Article  MATH  Google Scholar 

  54. Buscarino, A., Famoso, C., Fortuna, L., Frasca, M.: A New Chaotic electro-mechanical oscillator. Int. J. Bifurc. Chaos. 26, 1650161 (2016). https://doi.org/10.1142/S0218127416501613

    Article  MathSciNet  MATH  Google Scholar 

  55. Salcedo, A., Alvarez, J.: Oscillations in first-order, continuous-time systems via time-delay feedback. Complexity 2018, 1–14 (2018). https://doi.org/10.1155/2018/2178031

    Article  MATH  Google Scholar 

  56. Choi, I.: Interactive exploration of a chaotic oscillator for generating musical signals in real-time concert performance. J. Frankl. Inst. 331, 785–818 (1994). https://doi.org/10.1016/0016-0032(94)90089-2

    Article  MATH  Google Scholar 

  57. Geiyer, D., Kauffman, J.L.: Chaotification as a means of broadband energy harvesting with piezoelectric materials. J. Vib. Acoust. Trans. ASME. 137, 1–8 (2015). https://doi.org/10.1115/1.4030024

    Article  Google Scholar 

  58. Buscarino, A., Fortuna, L., Frasca, M., Muscato, G.: Chaos does help motion control. Int. J. Bifurc. Chaos 17, 3577–3581 (2007). https://doi.org/10.1142/S0218127407019391

    Article  MATH  Google Scholar 

  59. Madan R.N.: Front matter. In: Chua’s circuit: a paradigm for chaos, pp. i–xliii. World Scientific (1993)

  60. Luo, Y., He, Z., Che, X., Zeng, B.: The research of mechanism synthesis based on mechanical fractional order chaos system methods. In: 2009 Fifth international conference on natural computation, pp. 509–512. IEEE (2009)

  61. Li, C., Xu, L., Zhang, J.: Bifurcation and chaotic vibration for an electro-mechanical integrated harmonic piezodrive system. J. Mech. Sci. Technol. 30, 2961–2970 (2016). https://doi.org/10.1007/s12206-016-0605-8

    Article  Google Scholar 

  62. Lu, K., Yang, Q., Chen, G.: Singular cycles and chaos in a new class of 3D three-zone piecewise affine systems. Chaos 29, 043124 (2019). https://doi.org/10.1063/1.5089662

    Article  MathSciNet  MATH  Google Scholar 

  63. Natiq, H., Said, M.R.M., Ariffin, M.R.K., He, S., Rondoni, L., Banerjee, S.: Self-excited and hidden attractors in a novel chaotic system with complicated multistability. Eur. Phys. J. Plus. 133, 1–2 (2018). https://doi.org/10.1140/epjp/i2018-12360-y

    Article  Google Scholar 

  64. Ablay, G.: Chaos in PID controlled nonlinear systems. J. Electr. Eng. Technol. 10, 1843–1850 (2015). https://doi.org/10.5370/JEET.2015.10.4.1843

    Article  Google Scholar 

  65. Strogatz, S.H.: Nonlinear dynamics and chaos: with applications to physics, biology, chemistry, and engineering, 2nd edn. Westview Press, Boulder (2015)

    MATH  Google Scholar 

  66. Friedrich, H., Nayfeh, A.H.: Introduction to perturbation techniques. Wiley, New York. XIV, 519 S., £ 16.00. ISBN 0–471–08033–0. ZAMM - Zeitschrift für Angew. Math. und Mech. 61, 666–666 (1981). https://doi.org/10.1002/zamm.19810611224

Download references

Funding

Not Applicable.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shyamal Chatterjee.

Ethics declarations

Conflict of interest

No conflict of interest.

Additional information

Publisher's Note

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

Appendices

Appendix A

The Jacobian of the system at the static equilibrium is given by

$$ J = \left[ {\begin{array}{*{20}c} 0 & 1 & 0 & 0 \\ { - 1} & { - 2\zeta } & {\delta k_{c} } & 0 \\ 0 & 0 & 0 & 1 \\ { - 1} & { - 2\zeta } & {\delta k_{c} - \omega_{f}^{2} } & { - 2\zeta_{f} \omega_{f} } \\ \end{array} } \right]_{(y = 0,u = 0)} $$
(A-1)

The stability at the equilibrium point can be ascertained the eigenvalues of the Jacobian matrix. From this Jacobin matrix, one can write the characteristic equation as.

$$ a_{0} \lambda^{4} + a_{1} \lambda^{3} + a_{2} \lambda^{2} + a_{3} \lambda + a_{4} = 0, $$
(A-2)

where

$$ \begin{aligned} &a_{0} = 1, \hfill \\ &a_{1} = 2\zeta + 2\zeta_{f} \omega_{f} , \hfill \\ &a_{2} = 1 + \omega_{f}^{2} - \delta k_{c} + 4\omega_{f} \zeta_{f} \zeta , \hfill \\ &a_{3} = 2\omega_{f} \zeta_{f} + 2\omega_{f}^{2} \zeta , \hfill \\ &a_{4} =\omega_{f}^{2} \end{aligned} $$

According to the Routh–Hurwitz criterion, the system is called asymptotically stable when all the principal minors are positive and nonzero of the Hurwitz (H) matrix.

$$ H = \left[ {\begin{array}{*{20}c} {a_{1} } & {a_{3} } & 0 & 0 \\ {a_{0} } & {a_{2} } & {a_{4} } & 0 \\ 0 & {a_{1} } & {a_{3} } & 0 \\ 0 & 0 & {a_{2} } & {a_{4} } \\ \end{array} } \right] $$
(A-3)

The principal minors (\(\Delta\)) of the Hurwitz matrix are

$$ \begin{aligned} &\Delta_{1} = a_{1} , \hfill \\ &\Delta_{2} = a_{1} a_{2} - a_{0} a_{3} , \hfill \\ &\Delta_{3} = a_{1} a_{2} a_{3} - a_{0} a_{3}^{2} - a_{1}^{2} a_{4} , \hfill \\ &\Delta_{4} = a_{1} a_{2} a_{3} a_{4} - a_{1}^{2} a_{4}^{2} - a_{0} a_{3}^{2} a_{4} . \end{aligned} $$

Here, the values of \(a_{0} ,a_{1} ,a_{3} ,a_{4}\) are positive for any positive value the \(\omega_{f} ,\zeta_{f} ,\zeta\). But the sign of \(a_{2}\) depends on the sign of \(k_{c}\). If \(k_{c} > 0\), \(a_{2}\) will be negative (as \(\delta \gg 1\)) and vice-versa. Thus, all the principal minors are positive for \(k_{c} < 0\) which signifies that the static equilibrium of the system is stable. All principal minors are negative except \(\Delta_{1}\) for \(k_{c} > 0\) signifying the instability of the static equilibrium.

Appendix B

Here the stability of the limit cycle oscillation is established. The steady-state solution of the modulation equations Eqs. (24)–(26) is

$$ A_{s} = \frac{{( - 2\overline{{k_{c} }} \sin \Psi_{s} )}}{{\pi \overline{\zeta } }} $$
(B-1)
$$ B_{s} = \frac{{( - A\overline{{k_{s} }} \sin \Psi_{s} )}}{{2\overline{{\zeta_{f} }} \omega_{f} }} $$
(B-2)
$$ \sin \Psi_{s} = \frac{ - 1}{{\sqrt {1 + \left( {\frac{{2\zeta + 2\zeta_{f} \omega_{f} }}{{(\omega_{f}^{2} - 1)}}} \right)^{2} } }} $$
(B-3)

The Jacobian of the flow at the steady-state solution is obtained from Eqs. (27)–(29) as

$$ J = \left[ {\begin{array}{*{20}c} { - \zeta } & 0 & {\frac{{ - 2k_{c} \cos \Psi_{s} }}{\pi }} \\ {\frac{{ - \sin \Psi_{s} }}{2}} & { - \zeta_{f} \omega_{f} } & {\frac{{ - A_{s} \cos \Psi_{s} }}{2}} \\ {\frac{{2k_{c} \cos \Psi_{s} }}{{A_{s}^{2} \pi }} - \frac{{\cos \Psi_{s} }}{{2B_{s} }}} & {\frac{{A\cos \Psi_{s} }}{{2B_{s}^{2} }}} & {\frac{{2k_{c} \sin \Psi_{s} }}{{A_{s} \pi }} + \frac{{A_{s} \sin \Psi_{s} }}{{2B_{s} }}} \\ \end{array} } \right]_{{(A = A_{s} ,B = B_{s} ,\Psi = \Psi_{s} )}} $$
(B-4)

The characteristic equation of the Jacobian matrix can be written as

$$ b_{0} \lambda^{3} + b_{1} \lambda^{2} + b_{2} \lambda + b_{3} = 0 $$
(B-5)

where

$$ \begin{aligned} &b_{0} = 1 \hfill \\ &b_{1} = 2(\zeta + \omega_{f} \zeta_{f} ) \hfill \\ &b_{2} = (\zeta + \zeta_{f} \omega_{f} )^{2} + \zeta \zeta_{f} \omega_{f} + \{ (\zeta + \zeta_{f} \omega_{f} )^{2} + \zeta \zeta_{f} \} \{ \omega_{f}^{2} - 1\}^{2} /(4(\zeta + \zeta_{f} \omega_{f} )^{2} ) \hfill \\ &b_{3} = \omega_{f} \zeta \zeta_{f} \{ (\omega_{f}^{2} - 1)^{2} + (2\omega_{f} \zeta_{f} + 2\zeta )^{2} \} /(4(\zeta + \omega_{f} \zeta_{f} )) \end{aligned} $$

According to the Routh–Hurwitz criterion, the system response is asymptotically stable when all the principal minors of the Hurwitz (H) matrix are positive and nonzero. The Hurwitz matrix is written as

$$ H = \left[ {\begin{array}{*{20}c} {b_{1} } & {b_{3} } & 0 \\ {b_{0} } & {b_{2} } & 0 \\ 0 & {b_{1} } & {b_{3} } \\ \end{array} } \right] $$
(B-6)

and the principal minors are

$$ \begin{aligned} &\Delta_{1} = b_{1} , \hfill \\ &\Delta_{2} = b_{1} b_{2} - b_{0} b_{3} , \hfill \\ &\Delta_{3} = b_{1} b_{2} b_{3} - b_{0} b_{3}^{2} . \end{aligned} $$

All the principal minors are positive for \(\omega_{f} ,\zeta ,\zeta_{f} > 0\). Thus, it can be concluded that for \(k_{c} > 0\), the system response is stable.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Patel, B., Kundu, P.K. & Chatterjee, S. Nonlinear feedback anti-control of limit cycle and chaos in a mechanical oscillator: theory and experiment. Nonlinear Dyn 104, 3223–3246 (2021). https://doi.org/10.1007/s11071-021-06493-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11071-021-06493-1

Keywords

Navigation