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Adaptive sliding mode control for MIMO nonlinear systems based on fuzzy logic scheme

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Abstract

In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.

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References

  1. E. H. Mamdani, Applications of fuzzy algorithms for simple dynamic plants, Proceedings IEE, vol. 121, pp. 1585–1588, 1974.

    Google Scholar 

  2. L. A. Zadeh, Fuzzy sets, Information and Control, vol. 8, pp. 338–353, 1965.

    Article  MathSciNet  Google Scholar 

  3. S. V. Emelyanov, Variable Structure Control Systems, Moscow: Nauka(in Russian), 1967.

    Google Scholar 

  4. Y. Itkis, Control Systems of Variable Structure, New York: Wiley, 1976.

    Google Scholar 

  5. V. I. Utkin, Variable structure systems with sliding modes, IEEE Transactions on Automatic Control, vol. 22, no. 2, pp. 212–222, April, 1977.

    Article  MathSciNet  Google Scholar 

  6. J. Y. Hung, W. Gao, J. C. Hung, Variable structure control: a survey, IEEE Transaction on Industrial Electronics, vol. 40, no. 1, pp. 2–22, February, 1993.

    Article  Google Scholar 

  7. R. A. DeClarlo, S. H. Zak, G. R. Mathews, Variable structure control of nonlinear multivariable systems: A Tutorial, Proceedings of IEEE, vol. 76, no. 3, pp. 212–232, 1988.

    Article  Google Scholar 

  8. J. J. E. Slotine, W. P. Li, Applied Nonlinear Control, Prentice-Hall, Englewood Cliffs, NJ, 1991.

    MATH  Google Scholar 

  9. V. I. Utkin, Sliding Modes in Control Optimization, New York, Springer-Verlag, 1992.

    MATH  Google Scholar 

  10. A. S. I. Zinober, An introduction to sliding mode variable structure control, Variable Structure and Lyapunov Control, A. S. Zinoear (Ed.), London, UK: Springer-Verlag, 1994.

    Google Scholar 

  11. V. I. Utkin, VSS Premise in XX Century: Evidences of a witness, Proceedings of the 6th. IEEE International Workshop on Variable Structure Systems (VSS’ 2000), Gold Coast, Coolangatta, Australia, 7–9, December 2000.

  12. R. Palm, Sliding mode fuzzy control, Proceedings of IEEE Conference on Fuzzy Systems, San Diego, pp. 519–526, 1992.

  13. O. Kaynak, K. Erbatur, M. Ertugrul, The fusion of computationally intelligent methodologies and sliding-mode control: a survey, IEEE Transactions on Industrial Electronics, vol. 48, no. 1, pp. 4–17, February, 2001.

    Article  Google Scholar 

  14. J. Park, J. Kim, D. Park, LMI-based design of stabilizing fuzzy controllers for nonlinear systems described by Takagi-Sugeno fuzzy model, Fuzzy Sets and Systems, vol. 122, pp. 73–82, 2001.

    Article  MathSciNet  Google Scholar 

  15. W. Chang, J. B. Park, Y. H. Joo, G. Chen, Design of robust fuzzy-model-based controller with sliding mode control for SISO nonlinear systems, Fuzzy Sets and Systems, vol. 125, pp. 1–22, 2002.

    Article  MathSciNet  Google Scholar 

  16. F. Qiao, Q. M. Zhu, A. Winfield, C. Melhuish, Fuzzy sliding mode control for discrete time nonlinear systems, Computing Technology and Automation, vol. 22, no. 2, pp. 311–316, June, 2003.

    Google Scholar 

  17. K. J. Åström, B. Wittenmark, Adaptive Control, 2nd Ed., MA: Addison-Wesley, 1995.

    MATH  Google Scholar 

  18. W. M. Haddad, T. Hayakawa, V. Chellaboina, Robust adaptive control for nonlinear uncertain systems, Automatica, vol. 39, pp. 551–556, 2003.

    Article  MathSciNet  Google Scholar 

  19. L. X. Wang, Fuzzy Systems and Control, PTR Prentice Hall, Englewood Cliffs, New Jersey, 1994.

    Google Scholar 

  20. C. Y. Su, Y. Stepanenko, Adaptive control of a class of non-linear systems with fuzzy logic, IEEE Transactions on Fuzzy Systems, vol. 2, no. 4, pp. 285–294, November, 1994.

    Article  Google Scholar 

  21. B. Yoo, W. Ham, Adaptive fuzzy sliding mode control of non-linear system, IEEE Transactions on Fuzzy Systems, vol.6, no. 2, pp. 315–321, May, 1998.

    Article  Google Scholar 

  22. S. C. Tong, Q. G. Li, T. Y. Chai, Fuzzy adaptive control for a class of nonlinear systems, Fuzzy Sets and Systems, vol. 101, pp. 31–39, 1999.

    Article  MathSciNet  Google Scholar 

  23. T. Y. Chai, S. C. Tong, Fuzzy direct adaptive control for a class of nonlinear systems, Fuzzy Sets and Systems, vol. 103, pp. 379–387, 1999.

    Article  MathSciNet  Google Scholar 

  24. J. Wang, A. B. Rad, P. T. Chan, Indirect adaptive fuzzy sliding mode control, Part I: Fuzzy switching, Fuzzy Sets and Systems, vol. 122, pp. 21–30, 2001.

    Article  MathSciNet  Google Scholar 

  25. P. T. Chan, A. B. Rad, J. Wang, Indirect adaptive fuzzy sliding mode control, Part II: Parameter projection and supervisory control, Fuzzy Sets and Systems, vol. 122, pp. 31–443, 2001.

    Article  MathSciNet  Google Scholar 

  26. Y. C. Chang, Robust tracking control for nonlinear MIMO systems via fuzzy approaches, Automatica, vol. 36, pp. 1535–1545, 2000.

    Article  Google Scholar 

  27. H. X. Li, S. C. Tong, A hybrid adaptive fuzzy control for a class of nonlinear MIMO systems, IEEE Transactions on Fuzzy Systems, vol. 11, no. 1, pp. 24–34, February, 2003.

    Article  Google Scholar 

  28. S. C. Tong, H. X. Li, Fuzzy adaptive sliding mode control for MIMO nonlinear systems, IEEE Transactions on Fuzzy Systems, vol. 11, no. 3, pp. 354–360, June, 2003.

    Article  Google Scholar 

  29. S. Jagannathan, M. W. Vandegrift, F. L. Lewis, Adaptive fuzzy logic control of discrete-time dynamical systems, Automatica, vol. 36, pp. 229–241, 2000.

    Article  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. Intelligent Autonomous Systems Laboratory, Faculty of Computing, Engineering and Mathematical Sciences University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol, BS16 1QY, UK

    Feng Qiao, Quanmin Zhu, Alan FT Winfield & Chris Melhuish

Authors
  1. Feng Qiao
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  2. Quanmin Zhu
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  3. Alan FT Winfield
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  4. Chris Melhuish
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Corresponding author

Correspondence to Quanmin Zhu.

Additional information

Feng Qiao received the B.Eng. degree in electrical engineering and M.S.E. degree in systems engineering from the Northeastern University, Shenyang, China, in 1982 and 1987, respectively. During the period between 1987 and 2001, he worked at the Automation Research Institute of Metallurgical Industry (ARIM), Beijing, China, and he left ARIM on the post of a senior engineer in electrical and computer engineering. Now, he is a research PhD student at the University of the West of England, Bristol, UK, in intelligent modelling and control, his research interests include fuzzy logic systems, neural networks, nonlinear systems, stochastic systems, Kalman filter, sliding mode control, robust control, adaptive control, system identification, mathematical programming and optimisation, software development.

Quanmin Zhu is the Professor in control systems at the Faculty of Computing, Engineering and Mathematical Sciences (CEMS), University of the West of England (UWE), Bristol, UK. He had his higher education both in China and the UK, and obtained his PhD in Faculty of Engineering, University of Warwick, UK in 1989. His main research interest is in the area of nonlinear system modelling, identification, and control. Recently Dr Zhu started investigating electrodynamics of acupuncture points and sensory stimulation effects in human body, modelling of human meridian systems, and building up electro-acupuncture instruments. He has published over ninety papers on these topics.

Alan FT Winfield in 1984, shortly after completing a PhD in Digital Communications, Alan Winfield gave up his lectureship at the University of Hull to found a company on the newly established Hull Science Park. Dr Winfield went on to establish APD Communications Ltd as one of the key UK providers of software for safety-critical mobile radio systems. He left APD in 1991 to take up appointment as Associate Dean (Research) and Hewlett-Packard Professor of Electronic Engineering at the University of the West of England. Moving into the field of mobile robotics, he co-founded the Intelligent Autonomous Systems Laboratory in 1993. His work is centred on Control and Communications architectures for mobile robots. Current research has three strands: ad-hoc wireless connected robot swarms; autonomy in space robotics, and provably-stable intelligent control.

Chris Melhuish is Professor and Director of the Intelligent Autonomous Systems Laboratory of the University of the West of England (UWE). He has degrees in Geology from Durham University, an MSc in Computer Science from Bristol University and a PhD in collective robotics from UWE. He is a member of the British Computer Society and is a charactered engineer. His research interests include mobile robotics and in particular minimalist collective robotics, aerial robot formation control and robot energy autonomy.

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Qiao, F., Zhu, Q., Winfield, A.F. et al. Adaptive sliding mode control for MIMO nonlinear systems based on fuzzy logic scheme. Int J Automat Comput 1, 51–62 (2004). https://doi.org/10.1007/s11633-004-0051-4

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  • DOI: https://doi.org/10.1007/s11633-004-0051-4

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