Advertisement

Variable Structure Systems Theory in Computational Intelligence

  • Mehmet Önder Efe
  • Okyay Kaynak
  • Xinghuo Yu
Chapter
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 274)

Abstract

Intelligence in the form of well-organized solutions to the ill-posed problems has been the primary focus of many engineering applications. The ever-increasing developments in data fusion, sensor technology and high-speed microprocessors made the design in digital domain with high performance. A natural consequence of the progression during the last few decades is the emergence of computationally intelligent systems. Neural networks and fuzzy inference systems constitute the core approaches of computational intelligence, whose methods have extensively been used in the applications extending from image/pattern recognition to identification and control of nonlinear systems. This chapter is devoted to the analysis and design of learning strategies in the context of variable structure systems. Several approaches are discussed in detail with special emphasis on the sliding mode control of nonlinear systems.

Keywords

IEEE Transaction Lyapunov Function Fuzzy System Slide Mode Control Fuzzy Inference System 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Jang J.-S.R., Sun C.-T., Mizutani E. (1997) Neuro-Fuzzy and Soft Computing, PTR Prentice-HallGoogle Scholar
  2. 2.
    Berenji H. (1992) Fuzzy and Neural Control, In: P. J. Antsaklis, and K. M. Passino (Eds.), An Introduction to Intelligent and Autonomous Control, 215–236, Kluwer Academic Publishers, The NetherlandsGoogle Scholar
  3. 3.
    Hornik K. (1989) Multilayer Feedforward Networks are Universal Approximators, Neural Networks, 2, 359–366CrossRefGoogle Scholar
  4. 4.
    Funahashi, K. (1989) On the Approximate Realization of Continuous Mappings by Neural Networks, Neural Networks, 2, 183–192CrossRefGoogle Scholar
  5. 5.
    Cybenko G. (1989) Approximation by Superpositions of a Sigmoidal Function, Mathematics of Control, Signals, and Systems, 2, 303–314zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Haykin S. (1994) Neural Networks, Macmillan College Printing Company, New JerseyzbMATHGoogle Scholar
  7. 7.
    Gupta M.M., Rao D.H. (1993) Dynamical Neural Units with Applications to the Control of Unknown Nonlinear Systems, Journal of Intelligent and Fuzzy Systems, 1,1, 73–92Google Scholar
  8. 8.
    Wang Y-J., Lin C-T. (1998) Runge-Kutta Neural Network for Identification of Dynamical Systems in High Accuracy, IEEE Transactions on Neural Networks, 9,2, 294–307, MarchCrossRefGoogle Scholar
  9. 9.
    Zadeh L.A. (1965) Fuzzy Sets, Information and Control, 8, 338–353zbMATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    Wang L. (1997) A Course in Fuzzy Systems and Control, PTR Prentice-HallGoogle Scholar
  11. 11.
    Takagi T., and Sugeno M. (1985) Fuzzy Identification of Systems and Its Applications to Modeling and Control, IEEE Transactions on Systems, Man, and Cybernetics, 15,1, 116–132, JanuaryzbMATHGoogle Scholar
  12. 12.
    Rumelhart D.E., Hinton G.E., and Williams R.J. (1986) Learning Internal Representations by Error Propagation, in D. E. Rumelhart and J. L. McClelland, (Eds.), Parallel Distributed Processing: Explorations in the Microstructure of Cognition, 1, 318–362, MIT Press, Cambridge, M.A.Google Scholar
  13. 13.
    Hagan M. T., M. B. Menhaj (1994) Training Feedforward Networks with the Marquardt Algorithm, IEEE Transactions on Neural Networks, 5,6, 989–993, NovemberCrossRefGoogle Scholar
  14. 14.
    Emelyanov S. V. (1959) Control of First Order Delay Systems by means of an Astatic Controller and Nonlinear Correction, Automat. Remote Contr., 8, 983–991Google Scholar
  15. 15.
    Utkin V. I. (1977) Variable Structure Systems with Sliding Modes, IEEE Transactions Automatic Control, 22, 212–222zbMATHCrossRefMathSciNetGoogle Scholar
  16. 16.
    Young K. D., Utkin V. I., Ozguner U. (1999) A Control Engineer’s Guide to Sliding Mode Control, IEEE Transactions on Control Systems Technology, 7,3, 328–342, MayCrossRefGoogle Scholar
  17. 17.
    Hung J.Y., Gao W., Hung J. C. (1993) Variable Structure Control: A survey, IEEE Transactions on Industrial Electronics, 40,1, 1–9, FebruaryGoogle Scholar
  18. 18.
    Zinober A.S.I. (1994) (Ed), Variable Structure and Lyapunov Control, Springer-VerlagGoogle Scholar
  19. 19.
    Young K.K. (1993) (Ed), Variable Structure Control for Robotics and Aerospace Systems, Elsevier-ScienceGoogle Scholar
  20. 20.
    Utkin V.I. (1992) Sliding Modes in Control Optimization, Springer Verlag, New YorkzbMATHGoogle Scholar
  21. 21.
    Young K.D. (1978) Controller Design for a Manipulator Using Theory of Variable Structure Systems, IEEE Transactions on Systems, Man, and Cybernetics, SMC-8, 210–218Google Scholar
  22. 22.
    Slotine J.J.E., Sastry S.S. (1983) Tracking Control of Nonlinear Systems Using Sliding Surfaces with Application to Robot Manipulators, International Journal of Control, 38, 465–492zbMATHCrossRefMathSciNetGoogle Scholar
  23. 23.
    Hashimoto H., Maruyama K., Harashima F. (1987) A Microprocessor Based Robot Manipulator Control with Sliding Mode, IEEE Transactions on Industrial Electronics, 34, 11–18CrossRefGoogle Scholar
  24. 24.
    Wijesoma S.W. (1990) Robust Trajectory Following of Robots Using Computed Torque Structure with VSS, International Journal of Control, 52, 935–962zbMATHCrossRefGoogle Scholar
  25. 25.
    Denker A., Kaynak O. (1994) Application of VSC in Motion Control Systems, in Variable Structure and Lyapunov Control, A.S.I. Zinober (Ed.), Springer-Verlag, Chapter 17, 365–383Google Scholar
  26. 26.
    Kaynak O., Harashima F., Hashimoto H. (1984) Variable Structure Systems Theory, as applied to Sub-time Optimal Position Control with an Invariant Trajectory, Trans. IEE of Japan, Sec. E, 104, 47–52Google Scholar
  27. 27.
    Bartoszewicz A. (1988) On the Robustness of Variable Structure Systems in the Presence of Measurement Noise, Proc. IEEE Industrial Electronics Society Annual Conference, IECON’99, Aachen, Germany, 1733–1736, Aug. 31–Sept. 4Google Scholar
  28. 28.
    Slotine J.J.E., Li W. (1991) Applied Nonlinear Control, Englewood Cliffs, NJ: Prentice-HallzbMATHGoogle Scholar
  29. 29.
    Elmali, H., Olgac N. (1992) Robust Output Tracking Control of Nonlinear MIMO Systems via Sliding Mode Technique, Automatica, 28, 145–151CrossRefMathSciNetGoogle Scholar
  30. 30.
    Izosimov D. B., Utkin V. I. (1981) On Equivalence of Systems with Large Coefficients and Systems with Nonlinear Control, Automation and Remote Control, 11, 189–191Google Scholar
  31. 31.
    Tunay I., Kaynak O. (1996) Provident Control of an Electrohydraulic Servo with Experimental Results, Mechatronics, 6,3, 249–260CrossRefGoogle Scholar
  32. 32.
    Tunay I., Kaynak O. (1995) A New Variable Structure Controller for Affine Nonlinear Systems with Non-matching Uncertainties, International Journal of Control, 62,4, 917–939zbMATHCrossRefMathSciNetGoogle Scholar
  33. 33.
    Yen J., Langari R. (1999) Fuzzy Logic, PTR Prentice-Hall, New JerseyGoogle Scholar
  34. 34.
    Passino K.M., Yurkovich S. (1998) Fuzzy Control, Addison-Wesley, CaliforniaGoogle Scholar
  35. 35.
    Wang L.-X. (1994) Adaptive Fuzzy Systems and Control, Design and Stability Analysis, PTR Prentice-HallGoogle Scholar
  36. 36.
    Efe M.O., Kaynak O., Wilamowski B.M. (2000) Creating a Sliding Mode in a Motion Control System by Adopting a Dynamic Defuzzification Strategy in an Adaptive Neuro Fuzzy Inference System, Proc. IEEE Int. Conf. on Industrial Electronics, Control and Instrumentation, IECON-2000, Nagoya, Japan, 894–899, Oct. 22–28Google Scholar
  37. 37.
    Efe M.O., Kaynak O. (1999) A Comparative Study of Neural Network Structures in Identification of Nonlinear Systems, Mechatronics, 9,3, 287–300CrossRefMathSciNetGoogle Scholar
  38. 38.
    Sanner R.N., Slotine J.J.E. (1992) Gaussian Networks for Direct Adaptive Control, IEEE Transactions on Neural Networks, 3,6, 837–863CrossRefGoogle Scholar
  39. 39.
    Sira-Ramirez H., Colina-Morles E. (1995) A Sliding Mode Strategy for Adaptive Learning in Adalines, IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications, 42,12, 1001–1012, DecemberCrossRefGoogle Scholar
  40. 40.
    Hsu L., Real J.A. (1997) Dual Mode Adaptive Control Using Gaussian Neural Networks, Proc. of the 36th Conference on Decision and Control, (CDC), New Orleans, LA, 4032–4037Google Scholar
  41. 41.
    Hsu L., Real J.A. (1999) Dual Mode Adaptive Control, Proc. of the IFAC’99 World Congress, Beijing, K, 333–337Google Scholar
  42. 42.
    Yu X., Zhihong M., Rahman S.M.M. (1998) Adaptive Sliding Mode Approach for Learning in a Feedforward Neural Network, Neural Computing & Applications, 7, 289–294zbMATHCrossRefGoogle Scholar
  43. 43.
    Parma G.G., Menezes B.R., Braga A.P. (1998) Sliding Mode Algorithm for Training Multilayer Artificial Neural Networks, Electronics Letters, 34,1, 97–98, JanuaryCrossRefGoogle Scholar
  44. 44.
    Sira-Ramirez H., Colina-Morles E., Rivas-Echevverria F. (2000) Sliding Mode-Based Adaptive Learning in Dynamical-Filter-Weights Neurons, International Journal of Control, 73,8, 678–685zbMATHCrossRefMathSciNetGoogle Scholar
  45. 45.
    Efe M.O., Kaynak O., Yu X. (2000) Sliding Mode Control of a Three Degrees of Freedom Anthropoid Robot by Driving the Controller Parameters to an Equivalent Regime, Transactions of the ASME: Journal of Dynamic Systems, Measurement and Control, 122,4, 632–640, DecemberCrossRefGoogle Scholar
  46. 46.
    Efe M.O., Kaynak O. (2000) On Stabilization of Gradient Based Training Strategies for Computationally Intelligent Systems, IEEE Transactions on Fuzzy Systems, 8,5, 564–575, OctoberCrossRefGoogle Scholar
  47. 47.
    Efe M.O., Kaynak O., Wilamowski B.M. (2000) Stable Training of Computationally Intelligent Systems By Using Variable Structure Systems Technique, IEEE Transactions on Industrial Electronics, 47,2, 487–496, AprilCrossRefGoogle Scholar
  48. 48.
    Kaynak O., Erbatur K., Ertugrul M. (2001) The Fusion of Computationally Intelligent Methodologies and Sliding-Mode Control-A Survey, IEEE Transactions on Industrial Electronics, 48,1, 4–17, FebruaryCrossRefGoogle Scholar
  49. 49.
    Efe M.O. (2000) Variable Structure Systems Theory Based Training Strategies for Computationally Intelligent Systems, Ph.D. Dissertation, Bogazici UniversityGoogle Scholar
  50. 50.
    Yu X. Efe M.O., Kaynak O. (2001) A Backpropagation Learning Framework for Feedforward Neural Networks, in Proc. of the 2001 IEEE Int. Symposium on Circuits and Systems (ISCAS’01), III, pp. 700–702, May 6–9, Sydney, AustGoogle Scholar
  51. 51.
    Zhao Y. (1996) On-line Neural Network Learning Algorithm with Exponential Convergence Rate, Electronic Letters, 32,15, 1381–1382, JulyCrossRefGoogle Scholar
  52. 52.
    Bersini H., Gorrini V. (1997) A Simplification of the Backpropagation Through Time Algorithm for Optimal Neurocontroller, IEEE Transactions Neural Networks, 8,2, 437–441, MarchCrossRefGoogle Scholar
  53. 53.
    Erbatur K., Kaynak O., Sabanovic A. (1999) A Study on Robustness Property of Sliding Mode Controllers: A Novel Design and Experimental Investigations, IEEE Transactions on Industrial Electronics, 46,5, 1012–1018CrossRefGoogle Scholar
  54. 54.
    Roy R.G., Olgac N. (1997) Robust Nonlinear Control via Moving Sliding Surfaces-n-th Order Case, Proc. of the 36th Conference on Decision and Control, San Diego, California, U.S.A., December 943–948Google Scholar
  55. 55.
    Yilmaz C., Hurmuzlu Y. (2000) Eliminating the Reaching Phase from Variable Structure Control, Transactions of the ASME, Journal of Dynamic Systems, Measurement and Control, 122,4, 753–757, DecemberCrossRefGoogle Scholar
  56. 56.
    Hwang Y.R., Tomizuka M. (1994) Fuzzy Smoothing Algorithms for Variable Stucture Systems, IEEE Transactions on Fuzzy Systems, 2,4, 277–284CrossRefGoogle Scholar
  57. 57.
    Choi S.B., Kim M.S. (1997) New Discrete-Time Fuzzy-Sliding-Mode Control with Application to Smart Structures, Journal of Guidance Control and Dynamics, 20,5, 857–864zbMATHCrossRefGoogle Scholar
  58. 58.
    Erbatur K., Kaynak O., A. Sabanovic (1996) I. Rudas, Fuzzy Adaptive Sliding Mode Control of a Direct Drive Robot, Robotics and Autonomous Systems, 19,2, 215–227CrossRefGoogle Scholar
  59. 59.
    Chen C.S., Chen W.L. (1998) Robust Adaptive Sliding-Mode Control Using Fuzzy Modeling for an Inverted-Pendulum System, IEEE Transactions on Industrial Electronics, 45,2, 297–306CrossRefGoogle Scholar
  60. 60.
    Yu X., Man Z.H., Wu B.L. (1998) Design of Fuzzy Sliding-Mode Control Systems, Fuzzy Sets and Systems, 95,3, 295–306zbMATHCrossRefMathSciNetGoogle Scholar
  61. 61.
    Yoo B., Ham W. (1998) Adaptive Fuzzy Sliding Mode Control of Nonlinear System, IEEE Transactions on Fuzzy Systems, 6,2, 315–321CrossRefGoogle Scholar
  62. 62.
    Ha Q.P. (1996) Robust Sliding Mode Controller with Fuzzy Tuning, Electronics Letters, 32,17, 1626–1628CrossRefMathSciNetGoogle Scholar
  63. 63.
    Ha Q.P. (1997) Sliding Performance Enhancement with Fuzzy Tuning, Electronics Letters, 33,16, 1421–1423CrossRefMathSciNetGoogle Scholar
  64. 64.
    Ertugrul M., Kaynak O. (2000) Neuro Sliding Mode Control of Robotic Manipulators, Mechatronics, 10,1–2, 243–267Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Mehmet Önder Efe
    • 1
  • Okyay Kaynak
    • 2
  • Xinghuo Yu
    • 3
  1. 1.Electrical and Computer Engineering DepartmentCarnegie Mellon UniversityPittsburghUSA
  2. 2.Electrical and Electronic Engineering Department BebekBogazici UniversityIstanbulTurkey
  3. 3.Faculty of Informatics and CommunicationCentral Queensland UniversityRockhamptonAustralia

Personalised recommendations