Advertisement

Networked Predictive Control Based on Nonlinear Input–Output Model

  • Zhong-Hua Pang
  • Guo-Ping Liu
  • Donghua Zhou
  • Dehui Sun
Chapter

Abstract

In this chapter, a nonlinear networked predictive control method is presented for nonlinear systems described by a nonlinear autoregressive moving average model, where random network-induced delays, packet disorders, and packet dropouts in the feedback and forward channels are considered. In its implementation, the nonlinear model can be identified using an artificial neural network approach as an example. Numerical simulations and practical experiments are performed to confirm the effectiveness of the proposed method.

References

  1. 1.
    Liu, G.P.: Nonlinear Identification and Control: A Neural Network Approach. Springer, London (2001)Google Scholar
  2. 2.
    Pang, Z.H., Liu, G.P.: Model-based recursive networked predictive control. In: Proceedings of the 2010 IEEE International Conference on Systems, Man, and Cybernetics, pp. 1665–1670. (2010)Google Scholar
  3. 3.
    Peng, J., Dubay, R.: Identification and adaptive neural network control of a DC motor system with dead-zone characteristics. ISA Trans. 50(4), 588–598 (2011)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Zhong-Hua Pang
    • 1
  • Guo-Ping Liu
    • 2
  • Donghua Zhou
    • 3
  • Dehui Sun
    • 1
  1. 1.North China University of TechnologyBeijingChina
  2. 2.University of South WalesPontypriddUK
  3. 3.Shandong University of Science and TechnologyQingdaoChina

Personalised recommendations