AccScience Publishing / NSCE / Online First / DOI: 10.36922/NSCE026080006
RESEARCH ARTICLE

Complex dynamics, electrocardiogram-like waveform generation, and hardware implementation of an extended three-dimensional Van der Pol system with non-smooth nonlinearities

Jianning Huang1 Paul Didier Kamdem Kuate2* Ngamsa Tegnitsap Joakim Vianney3,4 Achille Ecladore Tchahou Tchendjeu5
Show Less
1 School of Mathematics and Information Science, Nanchang Normal University, Nanchang, Jiangxi, China
2 Department of Electrical and Power Engineering, Higher Technical Teachers Training College, University of Bamenda, Bambili, Northwest Region, Cameroon
3 Fotso-Victor University Institute of Technology, University of Dschang, Bandjoun, West Region, Cameroon
4 Department of Physics, Research Unit of Condensed Matter, Electronics, and Signal Processing, University of Dschang, Dschang, West Region, Cameroon
5 Department of Electrical and Electronic Engineering, National Polytechnic Institute, University of Bamenda, Bambili, Northwest Region, Cameroon
Received: 16 February 2026 | Revised: 4 April 2026 | Accepted: 9 April 2026 | Published online: 8 May 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

The Van der Pol (VdP) equation is a fundamental building block for modeling natural and engineering processes characterized by self-sustained oscillations. The present study introduces a novel three-dimensional autonomous chaotic system derived from a non-smooth extension of the classical VdP framework. The core innovation lies in the structural simplification of the nonlinear damping coefficient, replacing the standard quadratic term with a piecewise-linear absolute-value nonlinearity. This modification is coupled with the inclusion of a third state variable, modeled as a first-order dissipative system, which is fed back into the relaxation oscillator via a secondary absolute-value term. This topology significantly reduces computational overhead in hardware implementation while unlocking a higher-dimensional state-space. A comprehensive numerical analysis using bifurcation diagrams, Lyapunov exponent spectra, spectrograms, and Shannon entropy reveals complex dynamic behaviors, including chaos, antimonotonicity, and the coexistence of attractors. Furthermore, the proposed system can generate QRS-like waveforms that resemble human electrocardiogram patterns. The theoretical findings are validated through both an analog circuit implementation using off-the-shelf components and a digital realization on an STM32 microcontroller board using the Runge--Kutta numerical method. The agreement between numerical simulations, analog experiments, and digital implementation attests to the robustness of the proposed model across platforms for potential applications in biomedical signal emulation and chaos-based engineering.

Keywords
Modified Van der Pol
Chaotic dynamics
Antimonotonicity
Multistability
Electrocardiogram-like signal
Hardware implementation
Funding
None.
Conflict of interest
Paul Didier Kamdem Kuate is an Editorial Board Member of this journal, but was not in any way involved in the editorial and peer-review process conducted for this paper, directly or indirectly. Separately, other authors declared that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.
References
  1. Garrity T. Mathematics in nature: modeling patterns in the natural world. Math Intell. 2005;27(2):81-82. https://www.doi.org/10.1007/BF02985798.
  2. Van der Pol B. A theory of the amplitude of free and forced triode vibrations. Radio Rev. 1920;1(1):701-710, 754-762
  3. McMurran SL, Tattersall JJ. The mathematical collaboration of M. L. Cartwright and J. E. Littlewood. Am Math Mon. 1996;103(10):833-845. https://www.doi.org/10.2307/2974608.
  4. FitzHugh R. Impulses and physiological states in theoretical models of nerve membrane. Biophys J. 1961;1(6):445-466. https://www.doi.org/10.1016/S0006-3495(61)86902-6.
  5. Nagumo J, Arimoto S, Yoshizawa S. An active pulse transmission line simulating nerve axon. Proc IRE. 1962;50(10):2061-2070. https://www.doi.org/10.1109/JRPROC.1962. 288235.
  6. Cebrián-Lacasa D, Parra-Rivas P, Ruiz-Reynés D, Gelens L. Six decades of the FitzHugh–Nagumo model: a guide through its spatio-temporal dynamics and influence across disciplines. Phys Rep. 2024;1096:1-39. https://doi.org/10.1016/j.physrep.2024.09.014.
  7. Shinriki M, Yamamoto M, Mori S. Multimode oscillations in a modified Van Der Pol oscillator containing a positive nonlinear conductance. Proc IEEE. 1981;69(3):394-395. https://www.doi.org/10.1109/PROC.1981.11973.
  8. Ramadoss J, Kengne J, Tanekou ST, Rajagopal K, Kenmoe GD. Reversal of period doubling, multistability and symmetry breaking aspects for a system composed of a van der pol oscillator coupled to a duffing oscillator. Chaos Solitons Fractals. 2022;159:112157. https://www.doi.org/10.1016/j.chaos.2022.112157.
  9. Lyu W, Li S, Huang J, Bi Q. Occurrence of mixed-mode oscillations in a system consisting of a Van der Pol system and a Duffing oscillator with two potential wells. Nonlinear Dyn. 2024;112(8):5997-6013. https://www.doi.org/10.1007/s11071-024-09322-3.
  10. Viviani GL. Multiple potential well precision oscillators. IEEE Trans Circuits Syst II Express Briefs. 2021;68(8):2967-2971. https://www.doi.org/10.1109/TCSII.2021.3063362.
  11. Kuiate GF, Kingni ST, Tamba VK, Talla PK. Three-dimensional chaotic autonomous van der pol–duffing type oscillator and its fractional-order form. Chin J Phys. 2018;56(5):2560-2573. https://www.doi.org/10.1016/j.cjph.2018.08.003.
  12. Kengne R, Mbe JT, Fotsing J, et al. Dynamics and synchronization of a novel 4D-hyperjerk autonomous chaotic system with a Van der Pol nonlinearity. Z Naturforsch A. 2023;78(9):801-821. https://www.doi.org/10.1515/zna-2023-0063.
  13. Zhao H, Lin Y, Dai Y. Hidden attractors and dynamics of a general autonomous van der Pol–Duffing oscillator. Int J Bifurcat Chaos. 2014;24(06):1450080. https://www.doi.org/10.1142/S0218127414500801.
  14. Grasman J, Roerdink JBTM. Stochastic and chaotic relaxation oscillations. J Stat Phys. 1989;54:949-970. https://doi.org/10.1007/BF01019783.
  15. Ngouonkadi EBM, Fotsin HB, Louodop Fotso P. Implementing a memristive Van der Pol oscillator coupled to a linear oscillator: synchronization and application to secure communication. Phys Scr. 2014;89(3):035201. https://www.doi.org/10.1088/0031-8949/89/03/035201.
  16. Yang B, Wang Z, Tian H, Liu J. Symplectic dynamics and simultaneous resonance analysis of memristor circuit based on its van der Pol oscillator. Symmetry. 2022;14(6):1251. https://www.doi.org/10.3390/sym14061251.
  17. Ulonska S, Omelchenko I, Zakharova A, Schöll E. Chimera states in networks of Van der Pol oscillators with hierarchical connectivities. Chaos. 2016;26(9):094825. https://www.doi.org/10.1063/1.4962913.
  18. Shepelev IA, Bukh AV, Strelkova GI. Anti-phase synchronization of waves in a multiplex network of van der Pol oscillators. Chaos Solitons Fractals. 2022;162:112447. https://www.doi.org/10.1016/j.chaos.2022.112447.
  19. Shi F, Xu X, Liu X, et al. Complex neuronal dynamics under memristive electromagnetic radiation: modeling and digital signal processing implementation. Nonlinear Sci Control Eng. 2025;1(2):025400013. https://www.doi.org/10.36922/NSCE025400013.
  20. Grudzi ´nski K, ˙Zebrowski JJ. Modeling cardiac pacemakers with relaxation oscillators. Physica A. 2004;336(1–2):153–162. https://www.doi.org/10.1016/j.physa.2004.01.020.
  21. Elfouly MA. Improved mathematical models of Parkinson’s disease with Hopf bifurcation and Huntington’s disease with chaos. Acta Biotheor. 2024;72(3):1-29. https://www.doi.org/10.1007/s10441-024-09485-x.
  22. Shougat MREU, Perkins E. The van der Pol physical reservoir computer. Neuromorph Comput Eng. 2023;3(2):024004. https://www.doi.org/10.1088/2634-4386/acd20d.
  23. Rajaraman R. Nonlinear and fractional Van der Pol oscillators in cardiac rhythm modelling: a wavelet-based approach. Engineering Computations. 2025;42(9):3240-3274. https://www.doi.org/10.1108/EC-02-2025-0121.
  24. Zhang Z, Wu D. Real-time simulation for dynamics of multi-body robot based on a modified Rosenbrock method. In: 2023 IEEE 7th Information Technology and Mechatronics Engineering Conference (ITMEC). IEEE; 2023:2249-2253. https://www.doi.org/10.1109/ITOEC57671.2023.10291353.
  25. Jafari A, Hussain I, Nazarimehr F, Hashemi Golpayegani SMR, Jafari S. A simple guide for plotting a proper bifurcation diagram. Int J Bifurcat Chaos. 2021;31(01):2150011. https://www.doi.org/10.1142/S0218127421500115.
  26. Wolf A, Swift JB, Swinney HL, Vastano JA. Determining Lyapunov exponents from a time series. Physica D. 1985;16(3):285-317. https://www.doi.org/10.1016/0167-2789(85)90011-9.
  27. Ling BWK, Ho CYF, Tam PKS. Detection of chaos in some local regions of phase portraits using Shannon entropies. Int J Bifurcat Chaos. 2004;14(04):1493-1499. https://www.doi.org/10.1142/S0218127404010023.
  28. Tagne Fossi J, Kamdem Kuate PD, Folifack Signing VR, et al. Distributed estimation of sensor statistics using wireless networks of single-transistor chaotic oscillators. Nonlinear Dyn. 2025;113(21):30023-30055. https://www.doi.org/10.1007/s11071-025-11654-7.
  29. Dawson SP, Grebogi C, Yorke JA, Kan I, Koçak H. Antimonotonicity: inevitable reversals of period-doubling cascades. Phys Lett A. 1992;162(3):249-254. https://www.doi.org/10.1016/0375-9601(92)90442-O.
  30. Kyrianidis IM, Stouboulos IN, Haralabidis P, Bountis T. Antimonotonicity and chaotic dynamics in a fourth-order autonomous nonlinear electric circuit. Int J Bifurcat Chaos. 2000;10(08):1903-1915. https://www.doi.org/10.1142/S0218127400001171.
  31. Folifack Signing VR, Kengne J, Mboupda Pone JR. Antimonotonicity, chaos, quasi-periodicity and coexistence of hidden attractors in a new simple 4-D chaotic system with hyperbolic cosine nonlinearity. Chaos Solitons Fractals. 2019;118:187-198. https://www.doi.org/10.1016/j.chaos.2018.10.018.
  32. Pisarchik AN, Hramov AE. What is multistability. In: Multistability in Physical and Living Systems. Springer International Publishing; 2022:1-43. https://www.doi.org/10.1007/978-3-030-98396-3
  33. Ren X, Xu X, Liu X, et al. Memristor-coupled tabu learning neuron and multi-cavity control of attractors. Nonlinear Sci Control Eng. 2025;025400014. https://www.doi.org/10.36922/NSCE025400014.
  34. Kamdem Kuate PD, Tchendjeu AET, Fotsin H. A modified Rössler prototype-4 system based on Chua’s diode nonlinearity: dynamics, multistability, multiscroll generation and FPGA implementation. Chaos Solitons Fractals. 2020;140:110213. https://www.doi.org/10.1016/j.chaos.2020.110213.
  35. Szedlak P, Steele DS, Hopkins PM. Cardiac muscle physiology. BJA Educ. 2023;23(9):350-357. https://www.doi.org/10.1016/j.bjae.2023.05.004.
  36. Anbalagan T, Nath MK, Vijayalakshmi D, Anbalagan A. Analysis of various techniques for ECG signal in healthcare, past, present, and future. Biomed Eng Adv. 2023;6:100089. https://www.doi.org/10.1016/j.bea.2023.100089.
  37. Quiroz-Juárez MA, Rosales-Juárez JA, Jiménez-Ramírez O, Vázquez-Medina R, Aragón JL. ECG patient simulator based on mathematical models. Sensors. 2022;22(15):5714. https://www.doi.org/10.3390/s22155714.
  38. Goldberger AL, Amaral LAN, Glass L, et al. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation. 2000;101(23):e215–e220. https://www.doi.org/10.1161/01.CIR.101.23.e215.
  39. Pławiak P. ECG signals (1000 fragments) [Dataset]. Mendeley Data. 2017. https://data.mendeley.com/datasets/7dybx7wyfn.
Share
Back to top
Nonlinear Science and Control Engineering, Published by AccScience Publishing