Stable indirect adaptive fuzzy control for a class of SISO nonlinear systems

• Autorzy: Labiod S. , Boucherit M. S. , Bouhali O.
• Języki publikacji: EN

Abstrakty

EN

his paper proposed an indirect adaptive fuzzy control scheme for a class of unknown continuous-time nonlinear single-input single-output (SISO) dynamic systems. Within this scheme, the fuzzy systems are employed to approximate the unknown system dynamics. Based on these fuzzy approximations and a Lyapunov synthesis approach, suitable control laws and appropriate parameter adaptive algorithms are developed. It is shown that the proposed control scheme avoids the possible controller singularity problem, guarantes the convergence of the tracking error to zero and the global boundedness of all signals in the closed-loop system. Simulation results, performed on an inverted on a inverted pendulum system, are given to point out the good performance of the developed adaptive control approach.

Słowa kluczowe

EN

fuzzy control; fuzzy systems; nonlinear systems; adaptive control

• Wydawca: Polish Academy of Sciences, Committee of Automatic Control and Robotics
• Czasopismo: Archives of Control Sciences
• Rocznik: 2004
• Tom: Vol. 14, no. 1
• Strony: 27--43
• Opis fizyczny: Bibliogr. 18 poz.

Twórcy

autor

Labiod S.

• Process Control Laboratory, Department of Electrical Engineering Ecole Nationale Polytechnique 10, Ave Hassen Badi, BP.182, El Harrach, Algiers, Algieria

autor

Boucherit M. S.

• Process Control Laboratory, Department of Electrical Engineering Ecole Nationale Polytechnique 10, Ave Hassen Badi, BP.182, El Harrach, Algiers, Algieria

autor

Bouhali O.

• Process Control Laboratory, Department of Electrical Engineering Ecole Nationale Polytechnique 10, Ave Hassen Badi, BP.182, El Harrach, Algiers, Algieria

Bibliografia

• [1] Y. C. Chang: Adaptive fuzzy-based tracking control for nonlinear SISO systems via VSS and H∞ approaches. IEEE Trans. Fuzzy Syst., 9 (2001), 278-292.
• [2] S. Commuri and F. L. Lewis: Design and stability analysis of adaptive-fuzzy controller for a class of nonlinear systems. Proc. 35th CDC, (1996), 2729-2730.
• [3] A. Isidori: Nonlinear Control Systems. Springer-Verlag, Berlin, Germany, 1989.
• [4] J.S.R. Jang and C. T. Sun: Neuro-fuzzy modeling and control. Proc. IEEE, 83(3), (1995), 378-405.
• [5] P. Kokotovic and M. Arkac: Constructive nonlinear control: a historical perspective. Automatica, 37 (2001), 637-662.
• [6] K. M. Koo: Stable adaptive fuzzy controller with time-varying dead-zone. Fuzzy Sets and Systems, 121 (2001), 161-168.
• [7] M. Krstic, I. Kanellakopoulos and P. Kokotovic: Nonlinear and adaptive control design. New York, Weley Interscience, 1995.
• [8] S. Labiod and M. S. Boucherit: Direct stable fuzzy adaptive control of a class of SISO nonlinear systems. Archives of Control Sciences, 13(1) (2003), 95-110.
• [9] K. M. Passino and S. Yurkovich: Fuzzy Control. Addison-Wesley Longman Inc., 1998.
• [10] S. S. Sastry and A. Isidori: Adaptive control of linearizable systems. IEEE Trans. Automat. Contr., 34 (1989), 1123-1131.
• [11] J. E. Slotine and W. Li: Applied nonlinear control. Prentice Hall, Englewood Cliffs, NJ, 1991.
• [12] J. T. Spooner and K. M. Passino: Stable adaptive control using fuzzy systems and neural networks. IEEE Trans. Fuzzy Syst., 4 (1996), 339-359.
• [13] Y. C. Su and Y. Stepanenko: Adaptive control of a class of nonlinear systems with fuzzy logic. IEEE Trans. Fuzzy Systems, 2 (1994), 285-294.
• [14] Y. Tang, N. Zhang and Y. Li: Stable fuzzy adaptive control for a class of nonlinear systems. Fuzzy Sets and Systems, 104 (1999), 279-288.
• [15] S. H. Tong, Q. Li and T. Chai: Fuzzy adaptive control of a class of nonlinear systems. Fuzzy Sets and Systems, 101 (1999), 31-39.
• [16] L. X. Wang and J. M. Mendel: Generating fuzzy rules by learning from examples. Proc. IEEE Int. Symp. Intelligent Contr., (1991), 263-268.
• [17] L. X. Wang: Stable adaptive fuzzy control of nonlinear systems. Proc. 31st Conf. Dec. Contr., (1992), 2511-2516.
• [18] L. X. Wang: Fuzzy Systems and Control: Design and Stability Analysis. Prentice-Hall Inc., Englewood Cliffs, 1994.