Prespecified-time sliding mode control for stability of maglev train suspension systems

Lingling Zhang

Electronic Research Archive ›› 2026, Vol. 34 ›› Issue (3) : 1546 -1558.

PDF (742KB)
Electronic Research Archive ›› 2026, Vol. 34 ›› Issue (3) :1546 -1558. DOI: 10.3934/era.2026070
Research article
research-article
Prespecified-time sliding mode control for stability of maglev train suspension systems
Author information +
History +
PDF (742KB)

Abstract

This paper focuses on achieving prespecified-time stability in maglev suspension systems. Within a sliding mode control framework, we design three types of controllers for finite-time, fixed-time, and prespecified-time convergence. Pole assignment techniques are utilized to precisely tailor the system dynamics on the sliding manifold. The theoretical findings are validated through numerical simulations, which highlight the practical benefits of the proposed control strategies.

Keywords

maglev train / prespecified-time stability / Lyapunov approach / sliding mode control

Cite this article

Download citation ▾
Lingling Zhang. Prespecified-time sliding mode control for stability of maglev train suspension systems. Electronic Research Archive, 2026, 34 (3) : 1546-1558 DOI:10.3934/era.2026070

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Q. Zhu, S. M. Wang, Y. Q. Ni, A review of levitation control methods for low-and medium-speed maglev systems, Buildings, 14 (2024), 837. https://doi.org/10.3390/buildings14030837

[2]

H. W. Lee, K. C. Kim, J. Lee, Review of maglev train technologies, IEEE Trans. Magn., 42 (2006), 1917-1925. https://doi.org/10.1109/TMAG.2006.875842

[3]

L. Zhang, L. Huang, Hopf bifurcation analysis for a maglev system with two time delays, Mech. Syst. Signal Process., 224 (2025), 112006. https://doi.org/10.1016/j.ymssp.2024.112006

[4]

S. K. Kim, C. K. Ahn, Sensorless non-linear position-stabilising control for magnetic levitation systems, IET Control Theory Appl., 14 (2020), 2682-2687. https://doi.org/10.1049/ietcta.2020.0295

[5]

C. Chen, J. Xu, G. Lin, Y. Sun, F. Ni, Model identification and nonlinear adaptive control of suspension system of high-speed maglev train, Veh. Syst. Dyn., 60 (2022), 884-905. https://doi.org/10.1080/00423114.2020.1838564

[6]

F. Zhao, K. You, S. Song, W. Zhang, L. Tong, Suspension regulation of medium-low-speed maglev trains via deep reinforcement learning, IEEE Trans. Artif. Intell., 2 (2021), 341-351. https://doi.org/10.1109/TAI.2021.3097313

[7]

Y. Sun, J. Xu, G. Lin, W. Ji, L. Wang, RBF neural network-based supervisor control for maglev vehicles on an elastic track with network time delay, IEEE Trans. Ind. Inf., 18 (2020), 509-519. https://doi.org/10.1109/TII.2020.3032235

[8]

X. Bu, L. Wang, Y. Han, H. Liu, P. Hu, C. Cai, Dynamic model of high-speed maglev train-guideway bridge system with a nonlinear suspension controller, Adv. Struct. Eng., 27 (2024), 1328-1348. https://doi.org/10.1177/13694332241247921

[9]

B. Bidikli, An observer-based adaptive control design for the maglev system, Trans. Inst. Meas. Control, 42 (2020), 2771-2786. https://doi.org/10.1177/0142331220932396

[10]

Y. Sun, J. Xu, G. Lin, N. Sun, Adaptive neural network control for maglev vehicle systems with time-varying mass and external disturbance, Neural Comput. Appl., 35 (2023), 12361-12372. https://doi.org/10.1007/s00521-021-05874-2

[11]

H. Qiang, C. Xiao, H. Huang, Y. Hai, Y. Sun, Yaw feedback control of active steering vehicle based on differential flatness theory, J. Theor. Appl. Mech., 63 (2025), 131-149. https://doi.org/10.15632/jtam-pl/195727

[12]

Z. Zhang, Y. Pan, W. Zhao, J. Zhang, Z. Zi, Y. Xie, et al., Frequency analysis of a discrete-time fast nonlinear tracking differentiator algorithm based on isochronic region method, Electron. Res. Arch., 32 (2024), 5157-5175. https://doi.org/10.3934/era.2024238

[13]

R. Xu, U. Özgüner, Sliding mode control of a class of underactuated systems, Automatica, 44 (2008), 233-241. https://doi.org/10.1016/j.automatica.2007.05.014

[14]

L. Zhang, Z. Zhang, Z. Long, A. Hao, Sliding mode control with auto-tuning law for maglev system, Engineering, 2 (2010), 107-112. https://doi.org/10.4236/eng.2010.22015

[15]

C. Lei, Y. Lan, Z. Xu, Y. Sun, Fixed-time dual sliding mode control for linear synchronous motor maglev systems, Int. J. Robust Nonlinear Control, 34 (2024), 3781-3797. https://doi.org/10.1002/rnc.7162

[16]

Y. Liu, Y. Zhang, Y. Kao, Z. Gao, Sliding mode control for delta operator sampled systems, IEEE Trans. Autom. Sci. Eng., 22 (2025), 8006-8017. https://doi.org/10.1109/TASE.2024.3476085

[17]

Y. Gai, M. Chen, H. Wang, L. Wu, K. Peng, Fixed-time tracking control of quadrotor UAVs based on disturbance observer and sliding mode, Int. J. Syst. Sci., 57 (2026), 647-667. https://doi.org/10.1080/00207721.2025.2505714

[18]

F. Bayat, M. Javaheri, Two-layer terminal sliding mode attitude control of satellites equipped with reaction wheels, Asian J. Control, 22 (2020), 388-397. https://doi.org/10.1002/asjc.1878

[19]

S. P. Bhat, D. S. Bernstein, Finite-time stability of continuous autonomous systems, SIAM J. Control Optim., 38 (2000), 751-766. https://doi.org/10.1137/S0363012997321358

[20]

E. Moulay, W. Perruquetti, Finite time stability of differential inclusions, IMA J. Math. Control Inf., 22 (2005), 465-475. https://doi.org/10.1093/imamci/dni039

[21]

Y. Orlov, Finite time stability and robust control synthesis of uncertain switched systems, SIAM J. Control Optim., 43 (2005), 1253-1271. https://doi.org/10.1137/S0363012903425593

[22]

M. Forti, M. Grazzini, P. Nistri, L. Pancioni, Generalized Lyapunov approach for convergence of neural networks with discontinuous or non-Lipschitz activations, Physica D, 214 (2006), 88-99. https://doi.org/10.1016/j.physd.2005.12.006

[23]

A. Polyakov, Nonlinear feedback design for fixed-time stabilization of linear control systems, IEEE Trans. Autom. Control, 57 (2012), 2106-2110. https://doi.org/10.1109/TAC.2011.2179869

[24]

A. Polyakov, D. Efimov, W. Perruquetti, Finite-time and fixed-time stabilization: implicit Lyapunov function approach, Automatica, 51 (2015), 332-340. https://doi.org/10.1016/j.automatica.2014.10.082

[25]

F. Lopez-Ramirez, D. Efimov, A. Polyakov, W. Perruquetti, Conditions for fixed-time stability and stabilization of continuous autonomous systems, Syst. Control Lett., 129 (2019), 26-35. https://doi.org/10.1016/j.sysconle.2019.05.003

[26]

C. Chen, L. X. Li, H. P. Peng, Y. Yang, L. Mi, H. Zhao, A new fixed-time stability theorem and its application to the fixed-time synchronization of neural networks, Neural Networks, 123 (2020), 412-419. https://doi.org/10.1016/j.neunet.2019.12.028

[27]

Z. W. Cai, L. H. Huang, Z. Y. Wang, Finite-/fixed-time stability of nonautonomous functional differential inclusion: Lyapunov approach involving indefinite derivative, IEEE Trans. Neural Networks Learn. Syst., 33 (2022), 6763-6774. https://doi.org/10.1109/TNNLS.2021.3083396

[28]

C. D. Liang, M. F. Ge, Z. W. Liu, X. Zhang, J. H. Park, Predefined-time stabilization of T-S fuzzy systems: a novel integral sliding mode-based approach, IEEE Trans. Fuzzy Syst., 30 (2022), 4423-4433. https://doi.org/10.1109/TFUZZ.2022.3152834

[29]

Y. H. Ren, W. N. Zhou, Z. W. Li, Y. Q. Sun, Prescribed-time consensus tracking of multiagent systems with nonlinear dynamics satisfying time-varying Lipschitz growth rates, IEEE Trans. Cybern., 53 (2023), 2097-2109. https://doi.org/10.1109/TCYB.2021.3109294

[30]

F. C. Kong, H. L. Ni, Q. X. Zhu, C. Hu, T. Huang, Fixed-time and predefined-time synchronization of discontinuous neutral-type competitive networks via non-chattering adaptive control strategy, IEEE Trans. Network Sci. Eng., 10 (2023), 3644-3657. https://doi.org/10.1109/TNSE.2023.3271109

[31]

S. Z. Xie, Q. Chen, Predefined-time disturbance estimation and attitude control for rigid spacecraft, IEEE Trans. Circuits Syst. II Express Briefs, 71 (2024), 2089-2093. https://doi.org/10.1109/TCSII.2023.3331825

[32]

J. Liu, F. Yang, M. Zhang, Distributed dual-mode energy management for AC microgrids via prespecified-time dynamic event-triggered approach, IEEE Trans. Smart Grid, 17 (2026), 363-374. https://doi.org/10.1109/TSG.2025.3610227

[33]

L. Zhang, J. C. Ji, One-to-three resonant Hopf bifurcations of a maglev system, Nonlinear Dyn., 93 (2018), 1277-1286. https://doi.org/10.1007/s11071-018-4258-2

[34]

Y. Tang, Terminal sliding mode control for rigid robots, Automatica, 34 (1998), 51-56. https://doi.org/10.1016/S0005-1098(97)00174-X

[35]

Z. Cai, L. Huang, Z. Wang, Prespecified-time control of switched neural networks: novel Lyapunov approach of prespecified-time stability, Comput. Appl. Math., 43 (2024), 224. https://doi.org/10.1007/s40314-024-02748-w

PDF (742KB)

0

Accesses

0

Citation

Detail

Sections
Recommended

/

〈 〉