Coupling a machine vision sensor and a neural net supervised controller: controlling microbial cultivations

Qin Zhang, J. Bruce Litchfield, John F. Reid, Jinliang Ren, shiuan wu Chang

Research output: Contribution to journalArticlepeer-review


This paper describes the application of a machine vision sensor in a neural network-based supervisory control system for a microbial cultivation. The vision sensor was capable of counting the number of microbial cells and acquiring other microbial growth information like sporulation activities from the sample medium. The information was useful for classifying the state of the microbial cultivation and could be used for control and determination of nutrient addition. A neural network supervisory unit was used to tune PID controllers in order to obtain an optimal cellular growth environment throughout the process. The process was simulated with a neural network-based program and tested with a bench scale reactor. Promising results were obtained from both the computer simulation and experimental tests. The results suggest that application of machine vision sensors and neural network-based supervisory controls are attractive for microbial cultivations.

Original languageEnglish (US)
Pages (from-to)219-228
Number of pages10
JournalJournal of Biotechnology
Issue number3
StatePublished - Jan 31 1995


  • Fuzzy logic
  • Machine vision
  • Microbial cultivation control
  • Neural network

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Applied Microbiology and Biotechnology


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