Advertisement

Predictive Control Strategy of Hydraulic Turbine Turning System Based on BGNN Neural Network

  • Yijian Liu
  • Yanjun Fang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5370)

Abstract

A model predictive control (MPC) strategy based on a novel Bayesian-Gaussian neural network (BGNN) model was proposed for the controller design of hydraulic turbine in this paper. The BGNN was used to learn the nonlinear dynamic model of controlled hydraulic turbine on-line as the predictive model for the design of MPC controller. Experiments show that the proposed nonlinear MPC strategy based on BGNN performs much better than the conventional PID controller.

Keywords

Hydraulic Turbine BGNN Predictive Control neural network 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Jiang, C.: Nonlinear Simulation of Hydro turbine Governing System Based on Neural Network. In: IEEE International Conference on System, Man and Cybernetics, pp. 784–787 (1996)Google Scholar
  2. 2.
    Xu, F., Li, Z.: Computer Simulation about Hydraulic Generator Set. Hydraulic and Electric Power Press, Beijing (1998)Google Scholar
  3. 3.
    Prakash, J., Senthil, R.: Design of Observer Based nonlinear Model Predictive Controller for a Continuous Stirred Tank Reactor. Journal of Process Control 18, 504–514 (2008)CrossRefGoogle Scholar
  4. 4.
    Bellemans, T., De Schutter, B., De Moor, B.: Model Predictive Control for Ramp Metering of Motorway Traffic: a Case Study. Control Engineering Practice 14(5), 441–466 (2006)CrossRefGoogle Scholar
  5. 5.
    Blasco, X., Martinez, M., et al.: Model-Based Predictive Control of Greenhouse Climate for Reducing Energy and Water Consumption. Computer and Electronics in Agriculture 55(1), 49–70 (2007)CrossRefGoogle Scholar
  6. 6.
    Funahashi, K.: On the approximation of continuous mapping by neural networks. Neural Netw. 2, 183–192 (1989)CrossRefGoogle Scholar
  7. 7.
    Yazdan, S., Mohsen, H., Rostam, M.: Numerical Solution of the Nonlinear Schrodinger Equation by Feedforward Neural Networks. Communications in Nonlinear Science and Numerical Simulation 13(10), 2132–2145 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Jiang, C., Xiao, Z., Wang, S.: Neural Network Predict Control for the Hydro Turbine Generator Set. In: The Second International Conference on Machine Learning and Cybernetics, pp. 2–5 (2003)Google Scholar
  9. 9.
    Ye, H., Nicolai, R., Reh, L.: A Bayesian-Gaussian Neural Network and Its Application in Process Engineering. Chemical Engineering and Process 38, 439–449 (1998)CrossRefGoogle Scholar
  10. 10.
    Ye, H., Ni, W.: Nonliner System Identification Using a Bayesian-Gaussian Neural Network for Predictive Control. Neurocomputing 28, 21–36 (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Yijian Liu
    • 1
    • 2
  • Yanjun Fang
    • 1
  1. 1.Department of AutomationWuhan UniversityChina
  2. 2.School of Electrical & Automation EngineeringNanjing Normal UniversityJiangsuChina

Personalised recommendations