Model predictive control of time-delayed restraint system based on neurodynamical optimization

Yonggang Peng, Wei Wei, Jun Wang

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

In this paper, online optimization problem of model predictive control (MPC) of time-delayed system with restraints is described as an quadratic programming (QP) problem with restraints and a dual neural network is used to solve this problem.This neurodynamical optimization method exerts the advanteages of neural network that neural network can solve problems in parallelly and distributedly, and has fast optimization speed; and this method can be used to solve all kinds of complicated optimization problems with restraints. Experiment study results show that the proposed MPC method has good optimization precision and optimization speed, and this neurodynamical optimization method improves the online optimization capability of MPC.The proposed MPC method based on neurodynamical optimization extends the application fields of MPC.

Original languageEnglish
Pages (from-to)961-966
Number of pages6
JournalYi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument
Volume34
Issue number5
Publication statusPublished - May 2013
Externally publishedYes

Keywords

  • Model predictive control(MPC)
  • Neurodynamical optimization
  • Time-delayed system

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