Modelling and optimal control for a fed-batch fermentation process

Liu, Chongyang; Gong, Zhenfeng; Shen, Bangyu; Feng, Enmin

doi:10.1016/j.apm.2012.02.044

Cited by 54 publications

(43 citation statements)

References 37 publications

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“…Experimental data. Simulation using nonlinear multistage system in [26]. Simulation using nonlinear time−delay system.…”

Section: Theoremmentioning

confidence: 99%

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Sensitivity analysis and parameter identification for a nonlinear time-delay system in microbial fed-batch process

Liu

2014

Applied Mathematical Modelling

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a b s t r a c tDeveloping suitable dynamic models of bioprocess is a difficult issue in bioscience. In this paper, considering the microbial metabolism mechanism, i.e., the production of new biomass is delayed by the amount of time it takes to metabolize the nutrients, in glycerol bioconversion to 1,3-propanediol, we propose a nonlinear time-delay system to formulate the fed-batch fermentation process. Some important properties are also discussed. Then, in view of the effect of time-delay and the high number of kinetic parameters in the system, the parametric sensitivity analysis is used to determine the key parameters. Finally, a parameter identification model is presented and a global optimization method is developed to seek the optimal key parameters. Numerical results show that the nonlinear time-delay system can describe the fed-batch fermentation process reasonably.

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“…Experimental data. Simulation using nonlinear multistage system in [26]. Simulation using nonlinear time−delay system.…”

Section: Theoremmentioning

confidence: 99%

“…Experimental data. Simulation using nonlinear multistage system in [26]. was performed for eight times in the computation process.…”

Section: Theoremmentioning

confidence: 99%

Sensitivity analysis and parameter identification for a nonlinear time-delay system in microbial fed-batch process

Liu

2014

Applied Mathematical Modelling

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“…where γ > 0 is an adjustable parameter. Hence, with this approximation scheme, constraint (10) is approximated by canonical constraint (16). This constraint is a standard constraint and can be readily handled using the gradientbased technique.…”

Section: Constraint Transcriptionmentioning

confidence: 99%

“…To solve each of the resulting SOO problems by using gradient-based optimization techniques, the gradients of objective functions (12) and (13) as well as the gradients of constraint functions (8), (14) and (16) are needed. For the gradients of objective function (13) and constraint function (14) with respect to the decision variable ν, they can be easily calculated.…”

Section: Gradient Formulasmentioning

confidence: 99%

“…Thus, the fed-batch process is modelled as a nonlinear multistage system in [14]. Again, taking the concentration of 1,3-PD at the terminal time as the objective function, dynamic optimization problems involving the nonlinear multistage system were discussed in [14,15,16]. However, time-delays are ignored in the nonlinear systems mentioned above.…”

Section: Introductionmentioning

confidence: 99%

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Multi-objective optimization of nonlinear switched time-delay systems in fed-batch process

Liu

Gong

Teo

et al. 2016

Applied Mathematical Modelling

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Maximization of productivity and minimization of consumption are two top priorities for biotechnological industry. In this paper, we model a fed-batch process as a nonlinear switched time-delay system. Taking the productivity of target product and the consumption rate of substrate as the objective functions, we present a multi-objective optimization problem involving the nonlinear switched time-delay system and subject to continuous state inequality constraints. To solve the multi-objective optimization problem, we first convert the problem into a sequence of single-objective optimization problems by using convex weighted sum and normal boundary intersection methods. A gradientbased single-objective solver incorporating constraint transcription technique is then developed to solve these single-objective optimization problems. Finally, a numerical example is provided to verify the effectiveness of the numerical solution approach. Numerical results show that the normal boundary intersection method in conjunction with the developed single-objective solver is more favourable than the convex weighted sum method.

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Multi‐rate observer design and optimal control to maximize productivity of an industry‐scale fermentation process

et al. 2022

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Chemical industries focus primarily on profitable operations, resulting in growing attention and advances in the field of digital twins and optimal control algorithms.However, most industries still struggle due to a lack of physical sensors, infrequent measurements, and asynchronous sampling. Thus, in this work, we have designed a multi-rate state observer for state estimation from plant measurements and developed a model predictive controller (MPC) that maximized the profitability of an industry-scale fermentation process (fermenter volume < 378,500 L).Additionally, as the fermentation process is complex due to the use of microorganisms, which cannot be accurately captured using a first-principles model, we utilize a previously developed hybrid model in the proposed MPC formulation.The MPC uses a GAMS-MATLAB framework to determine the optimal input profiles while considering practical process constraints. It is shown using multiple datasets, that the MPC can increase productivity while also decreasing the plant operating cost.

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Modelling and optimal control for a fed-batch fermentation process

Cited by 54 publications

References 37 publications

Sensitivity analysis and parameter identification for a nonlinear time-delay system in microbial fed-batch process

Sensitivity analysis and parameter identification for a nonlinear time-delay system in microbial fed-batch process

Multi-objective optimization of nonlinear switched time-delay systems in fed-batch process

Multi‐rate observer design and optimal control to maximize productivity of an industry‐scale fermentation process

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