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Output Based Fault Tolerant Control of Nonlinear Systems Using RBF Neural Networks

  • Min Wang
  • Donghua Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3498)

Abstract

In this paper, an output based fault tolerant controller using radius basis function (RBF) neural networks is proposed which eliminates the assumption that all the states are measured given in Polycarpou’s method. Inputs of the neural network are estimated states instead of measured states. Outputs of the neural network compensate the effect of a fault. The closed-loop stability of the scheme is established. An engine model is simulated in the end to verify the efficiency of the scheme.

Keywords

Nonlinear System Nonlinear Control System Output Feedback Control SISO System High Gain Observer 
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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References

  1. 1.
    Diao, Y.X., Passino, M.K.: Intelligent Fault-Tolerant Control Using Adaptive and Learning Methods. Control Eng. Practice 10, 801–817 (2002)CrossRefGoogle Scholar
  2. 2.
    Yang, G.H., Wang, J.L., Soh, C.B.: Reliable Nonlinear Control System Design by Using Strictly Redundant Control Elements. Int. J. Control 69, 315–328 (1998)zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Polycarpou, M.M.: Fault Accommodation of a Class of Multivariable Nonlinear Dynamical Systems Using a Learning Approach. IEEE Trans. Autom. Control 46, 736–742 (2001)zbMATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Zhang, X.D., Parisini, T., Polycarpou, M.M.: Adaptive Fault-Tolerant Control of Nonlinear Uncertain Systems: An Information-Based Diagnostic Approach. IEEE Trans. on Autom. Control 49, 1259–1274 (2004)CrossRefMathSciNetGoogle Scholar
  5. 5.
    Wang, H., Wang, Y.: Neural-Network-Based Fault-Tolerant Control of Unknown Nonlinear Systems. Control Theory and Applications 146, 389–398 (1999)CrossRefGoogle Scholar
  6. 6.
    Marino, R., Tomei, P.: Observer-Based Adaptive Stabilization for a Class of Nonlinear Systems. Automatica 28, 787–793 (1992)zbMATHCrossRefMathSciNetGoogle Scholar
  7. 7.
    Kabore, P., Wang, H.: Design of Fault Diagnosis Filters and Fault-Tolerant Control for a Class of Nonlinear Systems. IEEE Trans. on Autom. Control 46, 1805–1810 (2001)zbMATHCrossRefMathSciNetGoogle Scholar
  8. 8.
    Seshagiri, S., Khalil, H.K.: Output Feedback Control of Nonlinear Systems Using RBF Neural Networks. IEEE Trans. Neural Netw. 11, 69–79 (2000)CrossRefGoogle Scholar
  9. 9.
    Isidori, A.: Nonlinear Control Systems: An Introduction. Lecture Notes in Control and Information Sciences, vol. 72. Springer, Heidelberg (1985)zbMATHCrossRefGoogle Scholar
  10. 10.
    Khalil, H.K.: Nonlinear Systems, 3rd edn. Prentice Hall, Upper Saddle River (2002)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Min Wang
    • 1
  • Donghua Zhou
    • 1
  1. 1.Department of AutomationTsinghua UniversityBeijingChina

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