Temperature control of fermentation bioreactor for ethanol production using IMC-PID controller

Kumar, M. Praveen; Prasad, G. Durga; Giri, Balendu Shekher; Singh, Ram Sharan

doi:10.1016/j.btre.2019.e00319

Cited by 38 publications

(26 citation statements)

References 26 publications

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“…The integral quadratic Performance Index, the same as the cost function shown in (19), was used for the comparative calculations. The same parameters of the Performance Index as for the PI-controller optimization were used to estimate the control quality (21). Disturbances and noise were added to the measured fermentation product variable to achieve the most realistic conditions, equal for both control systems.…”

Section: Discussionmentioning

confidence: 99%

“…Reference [20] comparatively shows the use of MPC and sliding mode control for temperature regulation in a batch bioreactor. Reference [21] shows temperature control of fermentation bioreactor for ethanol production using internal model control (IMC) based PID controller. Modified fractional-order IMC-PID for ethanol production is proposed in [22].…”

Section: Literature Reviewmentioning

confidence: 99%

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Adaptive Control of CO2 Production during Milk Fermentation in a Batch Bioreactor

Ritonja

2021

Mathematics

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The basic characteristic of batch bioreactors is their inability to inflow or outflow the substances during the fermentation process. This follows in the simple construction and maintenance, which is the significant advantage of batch bioreactors. Unfortunately, this characteristic also results in the inability of the current industrial and laboratory batch bioreactors to control fermentation production during the process duration. In some recent studies, it was shown that changing the temperature could influence the execution of the fermentation process. The presented paper shows that this phenomenon could be used to develop the closed-loop control system for the fermentation production control in batch bioreactors. First, based on theoretical work, experiments, and numerical methods, the appropriate structure of the mathematical model was determined and parameters were identified. Next, the closed-loop control system structure for batch bioreactor was proposed, and the linear and adaptive control system based on this structure and the derived and identified model were developed. Both modeling and adaptive control system design are new and represent original contributions. As expected, due to the non-linearity of the controlled plant, the adaptive control represents a more successful approach. The simulation and experimental results were used to confirm the applicability of the proposed solution.

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Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Adaptive Control of CO2 Production during Milk Fermentation in a Batch Bioreactor

Ritonja

2021

Mathematics

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“…The real-time investigation of closed loop depicted satisfactory tracking of the set point levels. Similar studies conducted using IMC-PID controller for temperature control in CSTR during ethanol production gave better results [41]. For another application involving improvement in biomass growth, combination of PI control with Generic Model Control (GMC) technique is implemented to fed batch cultivation of E. coli BL21(DE3).…”

Section: Proportional Integral/proportional Integral Derivative (Pi/pid) Controlmentioning

confidence: 94%

Bioprocess Control: Current Progress and Future Perspectives

Rathore

Mishra

Nikita

et al. 2021

Life

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Typical bioprocess comprises of different unit operations wherein a near optimal environment is required for cells to grow, divide, and synthesize the desired product. However, bioprocess control caters to unique challenges that arise due to non-linearity, variability, and complexity of biotech processes. This article presents a review of modern control strategies employed in bioprocessing. Conventional control strategies (open loop, closed loop) along with modern control schemes such as fuzzy logic, model predictive control, adaptive control and neural network-based control are illustrated, and their effectiveness is highlighted. Furthermore, it is elucidated that bioprocess control is more than just automation, and includes aspects such as system architecture, software applications, hardware, and interfaces, all of which are optimized and compiled as per demand. This needs to be accomplished while keeping process requirement, production cost, market value of product, regulatory constraints, and data acquisition requirements in our purview. This article aims to offer an overview of the current best practices in bioprocess control, monitoring, and automation.

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“…Studies on the design and analysis of PI controllers for the stabilization and regulation of CSTR reactors are abundant in the literature, which includes numerous successful applications [41,45,46].…”

Section: Pi Temperature Controlmentioning

confidence: 99%

A TITO Control Strategy to Increase Productivity in Uncertain Exothermic Continuous Chemical Reactors

2021

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In this manuscript, a two-input two-output (TITO) control strategy for an exothermic continuous chemical reactor is presented. The control tasks of the continuous chemical reactor are related to temperature regulation by a standard proportional-integral (PI) controller. The selected set point increases reactor productivity due to the temperature effect and prevents potential thermal runaway, and the temperature increases until it reaches isothermal operating conditions. Then, an optimal controller is activated to increase the mass reactor productivity. The optimal control strategy is based on a Euler-Lagrange framework, in which the corresponding Lagrangian is based on the model equations of the reactor, and the optimal controller is coupled with an uncertainty estimator to infer the unknown terms required by the proposed controller. As a benchmark, a continuous stirred tank reactor (CSTR) with a Van de Vusse chemical reaction is considered as an application case study. Notably, the proposed methodology is generally applicable to any continuous stirred tank reactor. The results of numerical experiments verify the satisfactory performance of the proposed control strategy.

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Temperature control of fermentation bioreactor for ethanol production using IMC-PID controller

Cited by 38 publications

References 26 publications

Adaptive Control of CO2 Production during Milk Fermentation in a Batch Bioreactor

Adaptive Control of CO2 Production during Milk Fermentation in a Batch Bioreactor

Bioprocess Control: Current Progress and Future Perspectives

A TITO Control Strategy to Increase Productivity in Uncertain Exothermic Continuous Chemical Reactors

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