Learning control of fermentation process with an improved DHP algorithm

Dazi Li; Ningjia Meng; Tianheng Song

doi:10.1016/j.cjche.2016.06.012

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Learning control of fermentation process with an improved DHP algorithm

Process Systems Engineering and Process Safety | Updated：2026-01-06

- Learning control of fermentation process with an improved DHP algorithm
- Chinese Journal of Chemical Engineering Vol. 24, Issue 10, Pages: 1399-1405(2016)
- Affiliations：
  
  Institute of Automation, Beijing University of Chemical Technology,Beijing,China,100029
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2016.06.012
  CLC：
- Published：2016
- Accepted：
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Dazi Li, Ningjia Meng, Tianheng Song. Learning control of fermentation process with an improved DHP algorithm[J]. , 2016, 24(10): 1399-1405.
DOI：

Dazi Li, Ningjia Meng, Tianheng Song. Learning control of fermentation process with an improved DHP algorithm[J]. , 2016, 24(10): 1399-1405. DOI： 10.1016/j.cjche.2016.06.012.

摘要

Abstract

Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system. However

ethanol fermentation processes exhibit complex behavior and nonlinear dynamics with respect to the cell mass

substrate

feed-rate

etc

. An improved dual heuristic programming algorithm based on the least squares temporal difference with gradient correction (LSTDC) algorithm (LSTDC-DHP) is proposed to solve the learning control problem of a fed-batch ethanol fermentation process. As a new algorithm of adaptive critic designs

LSTDC-DHP is used to realize online learning control of chemical dynamical plants

where LSTDC is commonly employed to approximate the value functions. Application of the LSTDC-DHP algorithmto ethanol fermentation process can realize efficient online learning control in continuous spaces. Simulation results demonstrate the effectiveness of LSTDC-DHP

and showthat LSTDC-DHP can obtain the near-optimal feed rate trajectory faster than other-based algorithms.

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