Vol.38, No.1, 2021, pp.65-77, doi:10.32604/csse.2021.016404
OPEN ACCESS
ARTICLE
Differential Evolution Algorithm Based Self-adaptive Control Strategy for Fed-batch Cultivation of Yeast
  • Aiyun Hu1, Sunli Cong1,*, Jian Ding2, Yao Cheng1, Enock Mpofu3
1 Jiangsu Key Lab of IoT Application Technology, Wuxi Taihu University, Wuxi, 214064, China
2 The key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, 214122, China
3 Department of Food Processing Technology, Harare Institute of Technology, Harare, Zimbabwe
* Corresponding Author: Sunli Cong. Email:
Received 01 January 2021; Accepted 02 February 2021; Issue published 01 April 2021
Abstract
In the fed-batch cultivation of Saccharomyces cerevisiae, excessive glucose addition leads to increased ethanol accumulation, which will reduce the efficiency of glucose utilization and inhibit product synthesis. Insufficient glucose addition limits cell growth. To properly regulate glucose feed, a different evolution algorithm based on self-adaptive control strategy was proposed, consisting of three modules (PID, system identification and parameter optimization). Performance of the proposed and conventional PID controllers was validated and compared in simulated and experimental cultivations. In the simulation, cultivation with the self-adaptive control strategy had a more stable glucose feed rate and concentration, more stable ethanol concentration around the set-point (1.0 g•L-1), and final biomass concentration of 34.5 g-DCW•L-1, 29.2% higher than that with a conventional PID control strategy. In the experiment, the cultivation with the self-adaptive control strategy also had more stable glucose and ethanol concentrations, as well as a final biomass concentration that was 37.4% higher than that using the conventional strategy.
Keywords
Saccharomyces cerevisiae; Ethanol accumulation; differential evolution algorithm; self-adaptive control
Cite This Article
A. Hu, S. Cong, J. Ding, Y. Cheng and E. Mpofu, "Differential evolution algorithm based self-adaptive control strategy for fed-batch cultivation of yeast," Computer Systems Science and Engineering, vol. 38, no.1, pp. 65–77, 2021.
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