Skip to main content
SpringerLink
Log in

Nonlinear system PID-type multi-step predictive control

  • Published:
Journal of Control Theory and Applications Aims and scope Submit manuscript

Abstract

A compound neural network was constructed during the process of identification and multi-step prediction. Under the PID-type long-range predictive cost function, the control signal was calculated based on gradient algorithm. The nonlinear controller’s structure was similar to the conventional PID controller. The parameters of this controller were tuned by using a local recurrent neural network on-line. The controller has a better effect than the conventional PID controller. Simulation study shows the effectiveness and good performance.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. K. S. Narendra, Neural network for control: theory and practice, Proceedings of the IEEE, Vol. 84, No. 10, pp. 1385–1406,1996.

    Article  Google Scholar 

  2. G. Prasad, E. Swidenbank, B. W. Hong, A neural net model-based multivariable long-range predictive control strategy applied in thermal power plant control, IEEE Trans, on Energy Conversion, Vol. 13, No. 2,pp. 176–182,1998.

    Article  Google Scholar 

  3. A. F. Atiya, S. I. Shaheen, A comparison between neural network forecasting techniques-ease study: River flow forecasting, IEEE Trans, on Neural Networks, Vol. 10, No. 2, pp. 402–409,1999.

    Article  Google Scholar 

  4. Z. Chen, H. Che, Z. Yuan, On the design and realization of PID-type long-range prediction self-tuning controller, Acta Scientiarum Naturalium University Nankaiensis, Vol. 28, No. 1, pp. 15–20,1995.

    Google Scholar 

  5. D. T. Pham, X. Liu, Training of Elman networks and dynamic system modeling, Int. J. Systems Science, Vol. 27, No. 2, pp. 221–226, 1996.

    Article  MATH  Google Scholar 

  6. D.W. Clarke, T. P. S Mohtadic, Generalized predictive control Part I and Part II, Automatica, Vol.23,No. 1,pp. 137–160,1987.

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Automation, Hebei University of Technology, 300130, Tianjin, China

    Yan Zhang

  2. Department of Automation, Nankai University, 300071, Tianjin, China

    Yan Zhang, Zengqiang Chen & Zhuzhi Yuan

Authors
  1. Yan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zengqiang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhuzhi Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

This work was supported by the National Natural Science Foundation of China (No. 60174021, No. 60374037) and the Science and Technology Greativeness Foundation of Nankai University.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhang, Y., Chen, Z. & Yuan, Z. Nonlinear system PID-type multi-step predictive control. J. Control Theory Appl. 2, 201–204 (2004). https://doi.org/10.1007/s11768-004-0070-2

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11768-004-0070-2

Keywords

Search

Navigation