Applying a Generalized Predictive Control Theory to a Carding Autoleveler

Yueyang Guo, Ruiqi Chen, Jinlian Hu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)


Usually, a carding process is difficult to control with classic control algorithms (such as PID) for three main reasons: strong stochastic disturbance, time delays, and parameter variation. In this paper, generalized predictive control (GPC) is introduced to control such a process. First, a CARIMA model is built to describe the carding process, then the GPC control law is derived and used to design the controller for a carding autoleveler. The simulation results show that the GPC controller can greatly reduce a sliver's standard deviation and can reject measured and unmeasured step disturbance. Although this paper mainly involves the design of a feedforward-feedback GPC controller for a carding autoleveler, the methods of modeling and GPC controller design can easily be extended to a feedback case and used to design controllers for other preparatory machines' autolev elers.
Original languageEnglish
Pages (from-to)755-761
Number of pages7
JournalTextile Research Journal
Issue number9
Publication statusPublished - 1 Jan 2003

ASJC Scopus subject areas

  • Chemical Engineering (miscellaneous)
  • Polymers and Plastics


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