Abstract
This work presents a dynamic fuzzy logic system based and stability oriented synthesis scheme for identification and adaptive control of nonlinear dynamic systems. First, a Dynamic Fuzzy Logic System structure (DFLS) is introduced. Following this, a DFLS based identification scheme is described, which was developed using the Lyapunov synthesis approach with a projection algorithm modification, and has been shown to be stable for a large class of nonlinear systems in the sense that all system parameters and variables are uniformly bounded. Further, a novel DFLS based indirect adaptive control scheme is developed using the same Lyapunov synthesis approach which is applicable to nonlinear systems in companion form. The system closed loop performance and stability properties are theoretically analyzed. Application of the identification and adaptive control algorithms to nonlinear dynamic systems is demonstrated by simulation examples which demonstrate that satisfactory results can be obtained under quite stringent conditions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Åström, K.J. and Wittenmank, B., Adaptive Control, Addison-Wesley Publishing Company, 1989.
Narendra, K.S. and Annaswamy, A.M., Stable Adaptive Systems, Engle-wood Cliffs, NJ: Prentice Hall, 1989.
Hornik, K., Stinchcombe, M., and White, H., “Multilayer Feedforward Networks are Universal Approximators”, Neural Networks, Vol.2, 359–366, 1989.
Wang, L. X., “Fuzzy Systems Are Universal Approximators”, San Diego, CA: Proceedings of IEEE International Conference on Fuzzy Systems, 1992, pp.1163–1170.
Lee, C. C., “Fuzzy Logic in Control Systems, Fuzzy Logic Controller-Part I and Part II”, IEEE Transactions on Systems, Man, and Cybernetics, Vol.20, No.2, 404–435, 1990.
Pedrycz, W., Fuzzy Control and Fuzzy Systems. 2nd, extended edition, Taunton, Somerset, England: Research Studies Press Ltd., 1993.
Pedrycz, W., Fuzzy Sets Engineering. Boca Raton, Ann Arbor, London, Tokyo: CRC Press, 1995.
Sugeno, M., Ed., Industrial Applications of Fuzzy Control, Amsterdam, North-Holland: Elsevier Science Publishers B.V., 1985.
Wang, L.X., “Stable Adaptive Control of Nonlinear Systems”, IEEE Transactions on Fuzzy Systems, Vol.1, No.2, 146–155, 1993.
Lee, J.X., and Vukovich, G., “The Dynamic Fuzzy Logic System: Nonlinear System Identification and Application to Robotic Manipulators”, accepted for publication in Journal of Robotic Systems, November 5, 1996.
Zadeh, L. A., “Outline of a New Approach to the Analysis of Complex Systems and Decision Processes”, IEEE Transactions on Systems, Man, and Cybernetics, Vol.SMC-3, 28–44, 1973.
Lee, J.X., Vukovich, G., and Sasiadek, J.Z., “Fuzzy Control of A Flexible Link Manipulator”, Baltimore: Proceedings of 1994 American Control Conference, June, 1994, pp.568–574.
Wang, L.X., and Mendel, J.M., “Fuzzy Basis Functions, Universal Approximation, and Orthogonal Least Squares Learning”, IEEE Transactions on Neural Networks, Vol.3, No.5, 807–814, September 1992.
Slotine, J.-J. E. and Li, W., Applied Nonlinear Control Englewood Cliffs, NJ: Prentice Hall, 1991.
Polycarpou, M.M., and Ioannou, P.A., “Stable Nonlinear System Identification Using Neural Network Models”, in Neural Networks in Robotics, Ed. by G. Bekey and K. Goldberg, Norwell, MA: Kluwer Academic Publishers, 1993, pp.147–164.
Goodwin, G.C., and Mayne, D.Q., “A Parameter Estimation Perspective of Continuous Time Model Reference Adaptive Control”, Automatica, Vol.23, 57–70, 1987.
Ioannou, P.A., and Datta, A., “Robust Adaptive Control: Design, Analysis and Robustness Bounds”, in Foundations of Adaptive Control, Ed. by P. V. Kokotovic, Berlin: Springer-Verlag, 1991, pp.71–152.
Lee, J.X., “Fuzzy Logic Systems: Nonlinear System Identification, Adaptive Control, and Application to Flexible Link Manipulators”, Ph.D. Dissertation, Carleton University, Ottawa, Canada, 1997.
Kailath, T., Linear Systems. Englewood Cliffs, NJ: Prentice-Hall, Inc, 1980.
Kosmatopoulos, E.B., Polycarpou, M.M., Christodoulou, M.A., and Ioannou, P.A., “High-Order Neural Network Structures for Identification of Dynamical Systems”, IEEE Transactions on Neural Networks, Vol.6, No.2, 422–431, March 1995.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1997 Springer Science+Business Media New York
About this chapter
Cite this chapter
Vukovich, G., Lee, J.X. (1997). Stable Identification and Adaptive Control - A Dynamic Fuzzy Logic System Approach. In: Pedrycz, W. (eds) Fuzzy Evolutionary Computation. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-6135-4_10
Download citation
DOI: https://doi.org/10.1007/978-1-4615-6135-4_10
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-7811-2
Online ISBN: 978-1-4615-6135-4
eBook Packages: Springer Book Archive