Predictive generic model control for non-linear interval systems with application in arc welding

Joseph Michael Istre, Yu Ming Zhang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


A control technique is proposed for a class of non-linear systems with parameter intervals. This technique can be considered as a modification of the Generic Model Control (GMC), which specifies the desired derivative of the output as a Proportional-Integral (PI) function of the error between the reference and the output. Specifically, to reduce unnecessary control variations and improve the suitability for the control of non-minimum phase systems, a multistep prediction is incorporated into the GMC, which in its original form is 'nearsighted', to develop a Predictive GMC (PGMC). For non-linear interval systems, interval arithmetic is used to analyse the interval of the input, which can guarantee the system's output stability defined by an output range. The PGMC is then derived for the interval non-linear system and an adaptive factor is proposed to improve the understanding of process dynamics and the performance of the closed-loop system. The resultant algorithm can control a non-linear system with parameter intervals and guarantee that the system's output will meet a specified criterion. A simulation has been done to demonstrate the effectiveness of the PGMC in reducing control signal variations. Also, an arc welding process has been controlled using the interval PGMC algorithm to demonstrate the effectiveness of the full-proposed control technique.

Original languageEnglish
Pages (from-to)140-150
Number of pages11
JournalInternational Journal of Modelling, Identification and Control
Issue number2
StatePublished - 2006


  • Arc welding
  • Generic Model Control (GMC)
  • Parameter interval
  • Predictive control
  • Robust control

ASJC Scopus subject areas

  • Modeling and Simulation
  • Computer Science Applications
  • Applied Mathematics


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