2D multi-model general predictive iterative learning control for semi-batch reactor with multiple reactions

Cui mei Bo, Lei Yang, Qing qing Huang, Jun Li, Fu rong Gao

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Batch to batch temperature control of a semi-batch chemical reactor with heating/cooling system was discussed in this study. Without extensive modeling investigations, a two-dimensional (2D) general predictive iterative learning control (2D-MGPILC) strategy based on the multi-model with time-varying weights was introduced for optimizing the tracking performance of desired temperature profile. This strategy was modeled based on an iterative learning control (ILC) algorithm for a 2D system and designed in the generalized predictive control (GPC) framework. Firstly, a multi-model structure with time-varying weights was developed to describe the complex operation of a general semi-batch reactor. Secondly, the 2D-MGPILC algorithm was proposed to optimize simultaneously the dynamic performance along the time and batch axes. Finally, simulation for the controller design of a semi-batch reactor with multiple reactions was involved to demonstrate that the satisfactory performance could be achieved despite of the repetitive or non-repetitive disturbances.

Original languageEnglish
Pages (from-to)2613-2623
Number of pages11
JournalJournal of Central South University
Volume24
Issue number11
DOIs
StatePublished - 1 Nov 2017

Keywords

  • general predictive control
  • iterative learning control
  • semi-batch reactor
  • two-dimensional system

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