Skip to main content
Log in

Optimal Control for Partially Observed Nonlinear Deterministic Systems with Fuzzy Parameters

  • Published:
Dynamics and Control

Abstract

In this paper we consider the control problem for a class of partially observed deterministic systems governed by nonlinear differential equations with fuzzy parameters. Using Takagi–Sugeno fuzzy model, we propose a linear (fuzzy) controller, driven by the output process, for controlling the system. Further, using calculus of variations, we have developed a set of necessary conditions on the basis of which optimal control can be determined. Based on these necessary conditions we have proposed a numerical algorithm for computing optimal control along with some numerical simulations to illustrate the effectiveness of the proposed (fuzzy) control scheme.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Ahmed, N. U., Elements of Finite Dimensional Systems and Control Theory, Longman Scientific & Technical: London, 1988.

    Google Scholar 

  2. Chen, B., Tseng, C., and Uang, H., “Robustness design of nonlinear systems via fuzzy linear control,” IEEE Transactions on Fuzzy Systems, vol. 7, no. 5, pp. 571–585, 1999.

    Google Scholar 

  3. Chen, G., Wang, J., and Sheih, L., “Interval Kalman filtering,” IEEE Transactions on Aerospace and Electrical Systems, vol. 33, pp. 250–259, 1997.

    Google Scholar 

  4. Chen, G., Xie, Q., and Sheih, L., “Fuzzy Kalman filtering,” Journal of Information Sciences, vol. 109, pp. 197–209, 1998.

    Google Scholar 

  5. Dabbous, T. E., “System identification using modified Laguerre model,” Ain Shams University, Scientific Bulletin, Cairo, Egypt, vol. 36, no. 2, pp. 387–400, 2001.

    Google Scholar 

  6. Dabbous, T. E., and Shafie, K. A., “Adaptive control of nonlinear systems using linear networks,” Scientific Bulletin, Ain Shams University, Cairo, Egypt, vol. 34, no. 4, pp. 437–451, 1999.

    Google Scholar 

  7. Hoskins, D., Hwang, J., and Vagners, J., “Iterative inversion of neural networks and its applications to adaptive control,” IEEE Transactions on Neural Networks, vol. 3, no. 2, pp. 292–301, 1992.

    Google Scholar 

  8. Ichikawa, Y. and Sawa, T., “Neural networks applications for direct feedback controllers,” IEEE Transactions on Neural Networks, vol. 3, no. 2, pp. 224–231, 1992.

    Google Scholar 

  9. Narendra, K. S. and Parthasarathy, K., “Identification and control of dynamical systems using neural networks,” IEEE Transaction on Neural Networks, vol. 1, no. 1, pp. 4–27, 1990.

    Google Scholar 

  10. Narendra, K. S. and Parthasarathy, K., “Gradient methods for optimization of dynamical systems containing neural networks,” IEEE Transactions on Neural Networks, vol. 2, no. 2, pp. 252–262, 1991.

    Google Scholar 

  11. Sastry, P., Santharama, G., and Unnikrishnan, K., “Memory neuron networks for identification and control of dynamical systems,” IEEE Transactions on Neural Networks, vol. 5, no. 2, pp. 306–319, 1994.

    Google Scholar 

  12. Seng, T., Khalid, M., and Yusof, R., “Tuning of a neuro fuzzy controller by genetic algorithm,” IEEE Transactions on System, Man and Cybernetics, Part B, vol. 29, no. 2, pp. 226–235, 1999.

    Google Scholar 

  13. Wang, L., Adaptive Fuzzy Systems and Control, Prentice Hall: Englewood Cliffs, NJ, 1994.

    Google Scholar 

  14. Wang, L. and Mendel, J., “Back propagation fuzzy system as nonlinear system identifier,” Proc. IEEE International Conference on Fuzzy Systems, San Diego, pp. 1409–1419, 1992.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dabbous, T.E., Bayoumi, M.S. Optimal Control for Partially Observed Nonlinear Deterministic Systems with Fuzzy Parameters. Dynamics and Control 11, 353–370 (2001). https://doi.org/10.1023/A:1020867121258

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1020867121258

Navigation