Sliding Mode Control of DC/DC Power Converters

  • Jianxing LiuEmail author
  • Yabin Gao
  • Yunfei Yin
  • Jiahui Wang
  • Wensheng Luo
  • Guanghui Sun
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 249)


In the previous chapters, we have successfully designed adaptive HOSM based observers for state observation and FDI of the PEM fuel cell systems. We now turn our attention towards the power side of the PEMFC. In fact, the PEMFC itself has severe dynamic limitations due to the time response of fuel flow and fuel delivery systems (hydrogen and air feed systems) [23]. In order for a PEMFC power system to be employed in varying load applications like electrical vehicles, storage elements with fast response time need to be integrated into the system.


  1. 1.
    Chen, C.L.P., Wen, G.X., Liu, Y.J., Wang, F.Y.: Adaptive consensus control for a class of nonlinear multiagent time-delay systems using neural networks. IEEE Trans. Neural Netw. Learn. Syst. 25(6), 1217–1226 (2014)CrossRefGoogle Scholar
  2. 2.
    Dijk, E.V., Spruijt, J., O’sullivan, D.M., Klaassens, J.B.: PWM-switch modeling of DC-DC converters. IEEE Trans. Power Electron. 10(6), 659–665 (1995)Google Scholar
  3. 3.
    Doncker, R.W.D., Divan, D.M., Kheraluwala, M.H.: A three-phase soft-switched high-power-density DC/DC converter for high-power applications. IEEE Trans. Ind. Appl. 27(1), 63–73 (1991)CrossRefGoogle Scholar
  4. 4.
    Gao, Q., Zeng, X.J., Feng, G., Wang, Y., Qiu, J.: T-S-fuzzy-model-based approximation and controller design for general nonlinear systems. IEEE Trans. Syst. Man Cybern. Part B: Cybern. 42(4), 1143–1154 (2012)CrossRefGoogle Scholar
  5. 5.
    Gao, W., Hung, J.C.: Variable structure control of nonlinear systems: a new approach. IEEE Trans. Ind. Electron. 40(1), 45–55 (1993)CrossRefGoogle Scholar
  6. 6.
    Juang, C.F., Huang, R.B., Cheng, W.Y.: An interval type-2 fuzzy-neural network with support-vector regression for noisy regression problems. IEEE Trans. Fuzzy Syst. 18(4), 686–699 (2010)CrossRefGoogle Scholar
  7. 7.
    Kazimierczuk, M.K.: Pulse-width Modulated DC-DC Power Converters. Wiley (2015)Google Scholar
  8. 8.
    Khanesar, M.A., Kayacan, E., Teshnehlab, M., Kaynak, O.: Extended Kalman filter based learning algorithm for type-2 fuzzy logic systems and its experimental evaluation. IEEE Trans. Ind. Electron. 59(11), 4443–4455 (2012)CrossRefGoogle Scholar
  9. 9.
    Lam, H., Xiao, B., Yu, Y., Yin, X., Han, H., Tsai, S.H., Chen, C.S.: Membership-function-dependent stability analysis and control synthesis of guaranteed cost fuzzy-model-based control systems. Int. J. Fuzzy Syst. 18(4), 537–549 (2016)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Lam, H.K., Li, H., Deters, C., Secco, E.L., Wurdemann, H.A., Althoefer, K.: Control design for interval type-2 fuzzy systems under imperfect premise matching. IEEE Trans. Ind. Electron. 61(2), 956–968 (2014)CrossRefGoogle Scholar
  11. 11.
    Lee, J.Y., Jeong, Y.S., Han, B.M.: An isolated DC/DC converter using high-frequency unregulated LLC resonant converter for fuel cell applications. IEEE Trans. Ind. Electron. 58(7), 2926–2934 (2011)CrossRefGoogle Scholar
  12. 12.
    Lin, Y.Y., Chang, J.Y., Lin, C.T.: A TSK-type-based self-evolving compensatory interval type-2 fuzzy neural network (TSCIT2FNN) and its applications. IEEE Trans. Ind. Electron. 61(1), 447–459 (2014)CrossRefGoogle Scholar
  13. 13.
    Lin, Y.Y., Liao, S.H., Chang, J.Y., Lin, C.T.: Simplified interval type-2 fuzzy neural networks. IEEE Trans. Neural Netw. Learn. Syst. 25(5), 959–969 (2014)CrossRefGoogle Scholar
  14. 14.
    Liu, J., Gao, Y., Luo, W., Wu, L.: Takagi-Sugeno fuzzy-model-based control of three-phase AC/DC voltage source converters using adaptive sliding mode technique. IET Control Theory Appl. 11(8), 1255–1263 (2016)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Liu, J., Gao, Y., Su, X., Wack, M., Wu, L.: Disturbance-observer-based control for air management of PEM fuel cell systems via sliding mode technique. IEEE Trans. Control Syst. Technol. 27(3), 1129–1138 (2019)CrossRefGoogle Scholar
  16. 16.
    Liu, J., Yin, Y., Luo, W., Vazquez, S., Franquelo, L.G.: Sliding mode control of a three-phase AC/DC voltage source converter under unknown load conditions: industry applications. IEEE Trans. Syst. Man Cybern.: Syst. 48(10), 1771–1780 (2018)CrossRefGoogle Scholar
  17. 17.
    Mendel, J.M.: Uncertain rule-based fuzzy systems. In: Introduction and New Directions, p. 684. Springer (2017)Google Scholar
  18. 18.
    Mendez-Diaz, F., Pico, B., Vidal-Idiarte, E., Calvente, J., Giral, R.: HM/PWM seamless control of a bidirectional buck-boost converter for a photovoltaic application. IEEE Trans. Power Electron. 34(3), 2887–2899 (2019)CrossRefGoogle Scholar
  19. 19.
    Morroni, J., Corradini, L., Zane, R., Maksimovic, D.: Adaptive tuning of switched-mode power supplies operating in discontinuous and continuous conduction modes. IEEE Trans. Power Electron. 24(11), 2603–2611 (2009)CrossRefGoogle Scholar
  20. 20.
    Oucheriah, S., Guo, L.: PWM-based adaptive sliding-mode control for boost DC-DC converters. IEEE Trans. Ind. Electron. 60(8), 3291–3294 (2013)CrossRefGoogle Scholar
  21. 21.
    Shen, L., Lu, D.D.C., Li, C.: Adaptive sliding mode control method for DC-DC converters. IET Power Electron. 8(9), 1723–1732 (2015)CrossRefGoogle Scholar
  22. 22.
    Sira-Ramirez, H.: Sliding-mode control on slow manifolds of DC-to-DC power converters. Int. J. Control 47(5), 1323–1340 (1988)MathSciNetCrossRefGoogle Scholar
  23. 23.
    Thounthong, P., Raël, S., Davat, B.: Control strategy of fuel cell and supercapacitors association for a distributed generation system. IEEE Trans. Ind. Electron. 54(6), 3225–3233 (2007)CrossRefGoogle Scholar
  24. 24.
    Utkin, V., Gulder, J., Shi, J.: Sliding mode control in electro-mechanical systems. In: Automation and Control Engineering Series, vol. 34. Taylor & Francis Group (2009)Google Scholar
  25. 25.
    Wai, R.J., Lin, Y.F., Liu, Y.K.: Design of adaptive fuzzy-neural-network control for a single-stage boost inverter. IEEE Trans. Power Electron. 30(12), 7282–7298 (2015)CrossRefGoogle Scholar
  26. 26.
    Wai, R.J., Shih, L.C.: Design of voltage tracking control for DC-DC boost converter via total sliding-mode technique. IEEE Trans. Ind. Electron. 58(6), 2502–2511 (2011)CrossRefGoogle Scholar
  27. 27.
    Wai, R.J., Shih, L.C.: Adaptive fuzzy-neural-network design for voltage tracking control of a DC-DC boost converter. IEEE Trans. Power Electron. 27(4), 2104–2115 (2012)CrossRefGoogle Scholar
  28. 28.
    Wang, D., Huang, J.: Neural network-based adaptive dynamic surface control for a class of uncertain nonlinear systems in strict-feedback form. IEEE Trans. Neural Netw. 16(1), 195–202 (2005)CrossRefGoogle Scholar
  29. 29.
    Wang, J.: A new type of fuzzy membership function designed for interval type-2 fuzzy neural network. Acta Autom. Sin. 43(8), 1425–1433 (2017)zbMATHGoogle Scholar
  30. 30.
    Wu, L., Gao, Y., Liu, J., Li, H.: Event-triggered sliding mode control of stochastic systems via output feedback. Automatica 48, 79–92 (2017)MathSciNetCrossRefGoogle Scholar
  31. 31.
    Yang, W.H., Huang, C.J., Huang, H.H., Lin, W.T., Chen, K.H., Lin, Y.H., Lin, S.R., Tsai, T.Y.: A constant-on-time control DC-DC buck converter with the pseudowave tracking technique for regulation accuracy and load transient enhancement. IEEE Trans. Power Electron. 33(7), 6187–6198 (2018)CrossRefGoogle Scholar
  32. 32.
    Yin, Y., Liu, J., Sanchez, J.A., Wu, L., Vazquez, S., Leon, J.I., Franquelo, L.G.: Observer-based adaptive sliding mode control of NPC converters: an RBF neural network approach. IEEE Trans. Power Electron. 34(4), 3831–3841 (2019)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Jianxing Liu
    • 1
    Email author
  • Yabin Gao
    • 1
  • Yunfei Yin
    • 1
  • Jiahui Wang
    • 2
  • Wensheng Luo
    • 1
  • Guanghui Sun
    • 1
  1. 1.School of AstronauticsHarbin Institute of TechnologyHarbinChina
  2. 2.College of AutomationHarbin Engineering UniversityHarbinChina

Personalised recommendations