Multi-objective optimal control of bioconversion process considering system sensitivity and control variation. (November 2022)

• Record Type: Journal Article
• Authors: Wang, Juan; Chen, Chihua; Ye, Jianxiong
• Is Part Of: Journal of process control. Volume 119(2022)
• Page Start: 13
• Page End: 24
• Publication Date: 2022-11
• Subjects: Multi-objective optimization -- Optimal control -- Continuous culture -- Competitive swarm optimization -- Large-scale optimization; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2022.09.006
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract: This paper aims to determine a time-varying dilution rate of the feed medium which maximizes mean productivity while minimizing both system sensitivity and control cost in glycerol continuous culture. A multi-objective optimal control problem subjected to a nonlinear control system and its auxiliary system is proposed and transformed into a finite-dimensional large-scale multi-objective optimization problem via discretization and time-scaling transformation. A multi-objective competitive swarm optimization algorithm is constructed to solve this transformed problem based on pairwise competition, mutation operation and environment selection. The Pareto front obtained shows the distribution of the optimal target value which indicates the rationality and feasibility of the control system under the approximate optimal strategy. Numerical simulations verify the robustness of the optimal control system and the effectiveness of our numerical solution method. The value of IGD shows the good accuracy and distribution of the proposed multi-objective optimization algorithm. Highlights: We propose a multi-objective optimal control problem of glycerol continuous culture. The multi-objective optimal control problem is approximated by a parameter optimization problem. A multi-objective competitive swarm optimization algorithm is developed. Numerical experiments show the effectiveness and applicability of the approach proposed.