Optimal minimal variation control with quality constraint for fed-batch fermentation processes involving multiple feeds

Yuan, Jinlong; Wang, Lei; Xie, Jun; Teo, Kok Lay

doi:10.1016/j.jfranklin.2020.04.007

Cited by 13 publications

(5 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A time-scaling transformation method [7,25,26] shall be applied to fix these switching instants by introducing a transform which maps from τ…”

Section: Time-scaling Transformation and Discretizationmentioning

confidence: 99%

“…Taking this into account, Liu et al proposed an open-loop switching system in which the feed rate of glycerol was the control function to maximize the concentration of 1,3-PD at terminal time [3]. Yuan et al took the feeding rates of glycerol and alkali as continuous control inputs to construct an optimal minimal variation control problem [7]. Gao et al proposed a nonlinear impulsive dynamical system with continuous variable impulsive instants and volumes of feeding glycerol and alkali [8].…”

mentioning

confidence: 99%

See 1 more Smart Citation

Determination of feeding rate ratio in coupled fed-batch fermentation with pH feedback considering limited number of switches

Chen

Wang

Zhao

et al. 2023

Journal of the Franklin Institute

View full text Add to dashboard Cite

“…A time-scaling transformation method [7,25,26] shall be applied to fix these switching instants by introducing a transform which maps from τ…”

Section: Time-scaling Transformation and Discretizationmentioning

confidence: 99%

mentioning

confidence: 99%

Determination of feeding rate ratio in coupled fed-batch fermentation with pH feedback considering limited number of switches

Chen

Wang

Zhao

et al. 2023

Journal of the Franklin Institute

View full text Add to dashboard Cite

“…In 2000, Xiu et al [6] proposed the dynamic model during the microbial transformation based on the Monod-type material balance equation and studied the multistability, but the infuence of superfuous substrates was not considered in this model. Yuan et al [7] considered an optimal minimal variation control and proposed a parallel algorithm based on the genetic algorithm and the gradients of the constraint functions with respect to decision variables. Te robust biobjective optimal control of 1, 3-PD microbial batch production process is researched in [8].…”

Section: Introductionmentioning

confidence: 99%

The Strong Stability of Optimal Nonlinear Dynamical System in Batch Fermentation

Wang

Tan

Gao

et al. 2022

Journal of Mathematics

View full text Add to dashboard Cite

For the bio-dissimilation of glycerol to 1,3-propanediol by Klebsiella pneumoniae, the nonlinear dynamical system of the complex metabolism in microbial batch fermentation is studied in this study. Since the analytical solution and equilibrium point cannot be found for the nonlinear dynamical system of batch fermentation, the system stability cannot be analyzed using general methods. Therefore, in this study, the stability of the system is analyzed from another angle. We present the corresponding linear variational system for the solution to the nonlinear dynamical system of complex metabolism. In addition, the boundedness of fundamental matrix solutions for the linear variational system is obtained. With this in mind, strong stability with respect to the perturbation of the initial state vector is proved for the nonlinear dynamical system of the complex metabolism.

show abstract

“…In recent years, many theoretical or practical researches on the dynamic optimization problem [13][14][15] were performed. Moreover, due to the complexity of aero-engine systems, it is difficult to give expressions of analytical solutions in the form of [16,17] by using methods, such as Pontryagin's extreme value principle or Bellman's dynamic programming. As a heuristic algorithm, the particle swarm optimization (PSO) algorithm can avoid solving gradient information, which is difficult to obtain.…”

Section: Introductionmentioning

confidence: 99%

Dynamic optimization with a non-smooth LPV system in aero-engine transition state acceleration process

2022

J. Nonlinear Var. Anal.

View full text Add to dashboard Cite

In this paper, we study the dynamic optimization of the acceleration process in the engine transition state. It is difficult for general linear and nonlinear models to portray the complex mechanical characteristics of an aero-engine. We consider a non-smooth linear parameter variation (LPV) system with nonlinear terms as a mathematical model for this acceleration process. First, a control parameterization method is used to transform the problem into a parameter selection problem. Then, a smoothing technique is used to deal with the non-smooth state constraints. Finally, in order to obtain the global optimal solution of this dynamic optimization problem, an optimization algorithm based on a combination of a gradient descent method and a modified particle swarm optimization is designed to solve the equivalent nonlinear programming problem. The effectiveness and superiority of the proposed algorithm is computationally verified by using the LPV model identified from the actual data.

show abstract

Optimal minimal variation control with quality constraint for fed-batch fermentation processes involving multiple feeds

Cited by 13 publications

References 41 publications

Determination of feeding rate ratio in coupled fed-batch fermentation with pH feedback considering limited number of switches

Determination of feeding rate ratio in coupled fed-batch fermentation with pH feedback considering limited number of switches

The Strong Stability of Optimal Nonlinear Dynamical System in Batch Fermentation

Dynamic optimization with a non-smooth LPV system in aero-engine transition state acceleration process

Contact Info

Product

Resources

About