NEURAL NETWORK BASED CONTROLLER FOR NONLINEAR AUTOMATIC GENERATION CONTROL

S. Z. Rizvi, M. S. Yousuf, H. N. Al-Duwaish

2010

Abstract

This paper presents an Artificial Neural Network (ANN) based controller design for nonlinear multivariable systems. The proposed method uses a novel algorithm for using and training a radial basis function (RBF) neural network based controller. The training algorithm makes sure that it does not violate any constraints on the inputs or outputs. Trajectory tracking results are presented for the challenging problem of nonlinear single area Automatic Generation Control (AGC) power system. Both linear and nonlinear cases are considered and robustness of the controller is tested as well.

References

  1. Al-Duwaish, H. N., Rizvi, S. Z. (2010). Neural network based controller for constrained multivariable systems. In 12th WSEAS Conference on Automatic Control, Modelling and Simulation ACMOS 2010, Italy, pages 104-109.
  2. Al-Hamouz, Z. M., Al-Duwaish, H. N. (2000). A new load frequency variable structure controller using genetic algorithms. In Electric Power Systems Research. volume 55, no. 1, pages 1-6.
  3. Chan, W. C., Hsu, Y. Y. (1981). Automatic generation control of interconnected power system using variable structure controllers. In Proceedings of the IEE Part C. volume 128, no. 5, pages 269-279.
  4. Cong, S., Liang, Y. (2009). Pid-like neural network nonlinear adaptive control for uncertain multivariable motion control systems. In IEEE Transaction on Industrial Electronics. volume 56, no. 10, pages 288-292.
  5. Hayakawa, T., Haddad, W., Hovakimyan, N. (2000). Neural network adaptive control for nonlinear uncertain dynamical systems with asymptotic stability guarantees. In IEEE American Control Conference, 2005, USA. pages 1301-1306.
  6. Hayakawa, T., Haddad, W., Volyanskyy, K. Y. (2008). Neural network hybrid adaptive control for nonlinear uncertain impulsive dynamical systems. In Nonlinear Analysis: Hybrid Systems. pages 862-874.
  7. Haykin, S. (1999). Neural Networks - A Comprehensive Foundation. Prentice-Hall, Second Edition.
  8. Kong, L., Xiao, L. (2007). A new model predictive control scheme-based load-frequency control. In IEEE International Conference on Control and Automation. volume 1, pages 2514-2518.
  9. Lu, J., Yahagi, T. (2000). Application of neural networks to nonlinear adaptive control systems. In IEEE International Cconference on Signal Processing, ICSP, 2000. pages 252-257.
  10. Pan, C. T., Liaw, C. M. (1989). An adaptive controller for power system and load frequency control. In IEEE Transactions on Power Systems. volume 4, no. 1, pages 122-128.
  11. Petre, E., Selisteanu, D., Sendrescu, D. (2008). Neural networks based adaptive control for a class of time varying nonlinear processes. In IEEE International Conference on Control, Automation and Systems, ICCAS, 2008, Korea. pages 1355-1360.
  12. Shayeghi, H., Shayanfar, H. A., Jalili, A. (2009). Load frequency control strategies: A state-of-the-art survey for the researcher. In Energy Conversion and Management. volume 50, no. 1, pages 344-353.
  13. Shijie, Y., Xu, W. (2009). Rbf neural network adaptive control of microturbine. In IEEE Global Congress on Intelligent Systems. pages 288-292.
  14. Shukla, D., Dawson, D. M., Paul, F. W. (1999). Multiple neural-network-based adaptive controller using orthonormal activation function neural networks. In IEEE Transaction on Neural Networks. volume 10, no. 6, pages 1494-1501.
  15. Smith, T. H., Boning, D. S. (1997). A self-tuning ewma controller utilizing artificial neural network function approximation techniques. In IEEE Transaction on Components, Packaging, and Manufacturing Technology, Part C. volume 20, no. 2, pages 121-132.
  16. Thapa, B. K., Jones, B., Zhu, Q. M. (2000). Non-linear control with neural networks. In Fourth International Conference on knowledge-based Intelligent Engineering Sys. & Allied Tech., 2000, U.K. pages 868-873.
  17. Velusami, S., Chidambaram, I. A. (2007). Decentralized biased dual mode controllers for load frequency control of interconnected power systems considering gdb and grc non-linearities. In Energy Conversion and Management.
  18. Wang, Y., Zhou, R., Wen, C. (1993). Robust load frequency controller design for power systems. In IEE Proceedings Part C. volume 140, no. 1, pages 11-16.
  19. Yang T. C., Cimen, H., Zhu, Q. M. (1998). Decentralised load-frequency controller design based on structured singular values. In IEE Proceedings on Generation, Transmission and Distribution. volume 145, no. 1, pages 7-14.
  20. Yang, Y., Wang, X. (2007). Adaptive h¥ tracking control for a class of uncertain nonlinear systems using radialbasis-function neural networks. In Neurocomputing. volume 70, pages 932-941.
  21. Yousuf, M. S., Al-Duwaish, H. N., Al-Hamouz, Z. M. (2010). PSO based predictive nonlinear automatic generation control. In 12th WSEAS Conference on Automatic Control, Modelling and Simulation ACMOS 2010, Italy, pages 87-92. In Press.
  22. Zayed, A. S., Hussain, A., Abdullah, R. A. (2006). A novel multiple-controller incorporating a radial basis function neural network based generalized learning model. In Neurocomputing. volume 69, pages 1868-1881.
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Paper Citation


in Harvard Style

Z. Rizvi S., S. Yousuf M. and N. Al-Duwaish H. (2010). NEURAL NETWORK BASED CONTROLLER FOR NONLINEAR AUTOMATIC GENERATION CONTROL . In Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010) ISBN 978-989-8425-32-4, pages 322-329. DOI: 10.5220/0003081503220329


in Bibtex Style

@conference{icnc10,
author={S. Z. Rizvi and M. S. Yousuf and H. N. Al-Duwaish},
title={NEURAL NETWORK BASED CONTROLLER FOR NONLINEAR AUTOMATIC GENERATION CONTROL},
booktitle={Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)},
year={2010},
pages={322-329},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003081503220329},
isbn={978-989-8425-32-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)
TI - NEURAL NETWORK BASED CONTROLLER FOR NONLINEAR AUTOMATIC GENERATION CONTROL
SN - 978-989-8425-32-4
AU - Z. Rizvi S.
AU - S. Yousuf M.
AU - N. Al-Duwaish H.
PY - 2010
SP - 322
EP - 329
DO - 10.5220/0003081503220329