Automation and Remote Control

, Volume 73, Issue 11, pp 1794–1807 | Cite as

Two-channel adaptive hybrid control of the air-to-fuel ratio and torque of automobile engines

  • S. A. Kolyubin
  • D. V. Efimov
  • V. O. Nikiforov
  • A. A. Bobtsov
Topical Issue


Combined feedforward/feedback control algorithm for highly nonlinear systems was proposed on the basis of the approximating hybrid model. The designed MIMO controller enables simultaneous control of the air-to-fuel ratio and torque for injector automobile engines. The theoretical results were validated experimentally with physical cars.


Torque Membership Function Remote Control Control Algorithm Hybrid Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Balluchi, A., Benvenuti, L., di Benedetto, M.D., et al., Automotive Engine Control and Hybrid Systems: Challenges And Opportunities, Proc. IEEE, 2000, vol. 88, no. 7, pp. 888–912.CrossRefGoogle Scholar
  2. 2.
    Butts, K., Kolmanovsky, I., Sivashankar, N., et al., Hybrid Systems in Automotive Control Applications, in Control Using Logic-Based Switching, Berlin: Springer-Verlag, 1997, pp. 173–189.CrossRefGoogle Scholar
  3. 3.
    Derong, L., Javaherian, H., Kovalenko, O., et al., Adaptive Critic Learning Techniques for Engine Torque and Air-Fuel Ratio Control, IEEE Trans. Syst., Man, Cybern., Part B: Cybern., 2008, vol. 38, no. 4, pp. 988–993.CrossRefGoogle Scholar
  4. 4.
    Dobner, D.J., A Mathematical Engine Model for Development of Dynamic Engine Control, SAE Paper 800054, 1980.Google Scholar
  5. 5.
    Bemporad, A., Giorgetti, N., Kolmanovsky, I.V., and Hrovat, D., A Hybrid System Approach to Modeling and Optimal Control of DISC Engines, in Proc. 41st IEEE Conf. Decision and Control, Las Vegas, Nevada, USA, 2002, pp. 1582–1587.Google Scholar
  6. 6.
    Druzhinina, M., Kolmanovsky, I., and Jing Sun, Hybrid Control of a Gasoline Direct Injection Engine, in Proc. 38th IEEE Conf. Decision and Control, 1999, vol. 3, pp. 2667–2672.Google Scholar
  7. 7.
    Jankovic, M. and Kolmanovsky, I., Constructive Lyapunov Control Design for Turbocharged Diesel Engines, IEEE Trans. Control Syst. Technol., 2000, vol. 8, no. 2, pp. 288–299.CrossRefGoogle Scholar
  8. 8.
    Kim, Y.-W., Rizzoni, G., and Utkin, V., Automotive Engine Diagnosis and Control via Nonlinear Estimation, IEEE Control Syst., 1998, vol. 18, no. 5, pp. 84–99.CrossRefGoogle Scholar
  9. 9.
    Rokusho, T. and Yamakita, M., Robust Combined Feedforward and Feedback Control for Start Up Engine Control, in IEEE Int. Conf. Control Appl., 2008, pp. 227–232.Google Scholar
  10. 10.
    Stotsky, A.A., Automotive Engines: Control, Estimation, Statistical Detection, Berlin: Springer, 2009.Google Scholar
  11. 11.
    Giryavets, A.K., Teoriya upravleniya avtomobil’nym benzinovym dvigatelem (Theory of Control of Automobile Gasoline Engine), Moscow: Stroiizdat, 1997.Google Scholar
  12. 12.
    Turin, R. and Geering, H., On-Line Identification of Air-to-Fuel Ratio Dynamics in a Sequentially Injected SI Engine, SAE Technical Paper 930857, 1993.Google Scholar
  13. 13.
    Dongyun Wang, Kai Wang, and Mingcong Deng, The Application Study of Intelligent PID Algorithm for the Internal Combustion Engine Control System, in Int. Conf. Mechatron. Automat. (ICMA), Aug. 4–7, 2010, pp. 923–927.Google Scholar
  14. 14.
    Zhao, F.-Q., Lai, M.-C., and Harrington, D.L., A Review of Mixture Preparation and Combustion Control Strategies for Spark-Ignited Direct-Injection Gasoline Engines, SAE J. Engines, 1997, vol. 106, no. 970627, pp. 861–904.Google Scholar
  15. 15.
    Gerasimov, D.N., Dzhavakherian, Kh., Efimov, D.V., et al., Injector Engine as a Control Plant. I. Engine Scheme and Design of the Mathematical Model, Izv. Ross. Akad. Nauk, Teor. Sist. Upravlen., 2010, no. 5, pp. 135–147.Google Scholar
  16. 16.
    Gerasimov, D.N., Dzhavakherian, Kh., Efimov, D.V., et al., Injector Engine as a Control Plant. II. Problem of Engine Automatic Control, Izv. Ross. Akad. Nauk, Teor. Sist. Upravlen., 2010, no. 6, pp. 170–181.Google Scholar
  17. 17.
    Lukanin, V.N., Morozov, K.A., Khachiyan, A.C., et al., Dvigateli vnutrennego sgoraniya. V 3 kn. Kn. 1 Teoriya rabochikh protsessov: Uch. dlya Vuzov (Internal Combustion Engines. in 3 books. Book 1: Theory of Operation), Lukanin, V.N., Ed., Moscow: Vysshaya Shkola, 2005, 2nd revised and completed ed.Google Scholar
  18. 18.
    Kolchin, A.I., Raschet avtomobil’nykh i traktornykh dvigatelei: ucheb. posobie dlya vuzov (Calculation of the Automobile and Tractor Engines. Textbook), Kolchin, A.I. and Demidov, V.P., Moscow: Vysshaya Shkola, 2003, 3rd revised and completed ed.Google Scholar
  19. 19.
    Heemels, W.P.M.H., Schutter, B.De, and Bemporad, A., Equivalence of Hybrid Dynamical Models, Automatica, 2001, vol. 37, pp. 1085–1091.zbMATHCrossRefGoogle Scholar
  20. 20.
    Bemporad, A., Efficient Conversion of Mixed Logical Dynamical Systems Into an Equivalent Piecewise Affine Form, IEEE Trans. Automat. Control, 2004, vol. 49, no. 5, pp. 832–838.MathSciNetCrossRefGoogle Scholar
  21. 21.
    Takagi, T. and Sugeno, M., Fuzzy Identification of Systems and its Applications to Modeling and Control, IEEE Trans. Syst., Man, Cybern., 1985, vol. 15, pp. 116–132.zbMATHCrossRefGoogle Scholar
  22. 22.
    Ljung, L., System Identification: Theory for the User, Englewood Cliffs: Prentice Hall, 1987. Translated under the title Identifikatsiya sistem. Teoriya dlya pol’zovatelya, Moscow: Nauka, 1991.zbMATHGoogle Scholar
  23. 23.
    Eykhoff, P., System Identification: Parameter and State Estimation, Chichester: Wiley, 1974. Translated under the title Osnovy identifikatsii sistem upravleniya: otsenivanie parametrov i sostoyaniya, Moscow: Mir, 1975.Google Scholar
  24. 24.
    Liberzon, D., Switching in Systems and Control, Boston: Birkhauser, 2003.zbMATHCrossRefGoogle Scholar
  25. 25.
    Efimov, D.V., Uniting Global and Local Controllers under Acting Disturbances, Automatica, 2006, vol. 42, pp. 489–495.MathSciNetzbMATHCrossRefGoogle Scholar
  26. 26.
    Krut’ko, P.D., Obratnye zadachi dinamiki v teorii avtomaticheskogo upravleniya. Tsikl lektsii: uch. posobie dlya vuzov (Lectures on the Inverse Problems of Dynamics in the Automatic Control Theory. Textbook), Moscow: Mashinostroenie, 2004.Google Scholar
  27. 27.
    Kapoor, N., Teel, A.R., and Daoutidis, P., An Anti-Windup Design for Linear Systems with Input Saturation, Automatica, 1998, vol. 34(5), pp. 559–574.MathSciNetzbMATHCrossRefGoogle Scholar
  28. 28.
    Sofrony, J., Anti-windup Compensation of Input Constrained Systems: Synthesis Using Riccati Equations, Saarbrücken: VDM Verlag, 2009.Google Scholar
  29. 29.
    Camacho, E. and Bordons, S., Model Predictive Control, New York: Springer, 2004.zbMATHCrossRefGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2012

Authors and Affiliations

  • S. A. Kolyubin
    • 1
  • D. V. Efimov
    • 2
  • V. O. Nikiforov
    • 1
  • A. A. Bobtsov
    • 1
  1. 1.National Research University of Information Technologies, Mechanics, and OpticsSt. PetersburgRussia
  2. 2.l’Institut National de Recherche en Informatique et en Automatique (INRIA)LilleFrance

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