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Chemical and Biochemical Engineering Quarterly, Vol. 31 No. 1, 2017.

Original scientific paper

https://doi.org/10.15255/CABEQ.2016.957

A Comparative Study of Temperature Optimal Control in a Solid State Fermentation Process for Edible Mushroom Growing

K. J. Gurubel ; Departamento de Ingenierías, Universidad de Guadalajara, CUTONALA, Tonalá, Jalisco, México, Avenida Nuevo Periférico No. 555, Ejido San José Tatepozco, C.P. 45425
A. Sanchez ; Departamento de Control Automático, CINVESTAV del IPN, Unidad Guadalajara, Zapopan, Jalisco, México Av. Del Bosque 1145, Col. El Bajío, CP. 45019
A. Coronado-Mendoza ; Departamento de Ingenierías, Universidad de Guadalajara, CUTONALA, Tonalá, Jalisco, México, Avenida Nuevo Periférico No. 555, Ejido San José Tatepozco, C.P. 45425
E. N. Sanchez ; Departamento de Control Automático, CINVESTAV del IPN, Unidad Guadalajara, Zapopan, Jalisco, México Av. Del Bosque 1145, Col. El Bajío, CP. 45019

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Abstract

In this paper, optimal control strategies for temperature trajectory determination in order to maximize thermophilic bacteria in a fed-batch solid-state fermentation reactor are proposed. This process is modeled by nonlinear differential equations, which has been previously validated experimentally with scale reactor temperature profiles. The dynamic input aeration rate of the reactor is determined to increase microorganisms growth of a selective substrate for edible mushroom cultivation. In industrial practice, the process is comprised of three thermal stages with constant input air flow and three types
of microorganisms in a 150-hour lapse. Scytalidium thermophilum and actinobacteria are desired in order to obtain a final biomass composition with acceptable microorganisms concentration. The Steepest Descent gradient algorithm in continuous time and the Gradient Projection algorithm in discrete-time are used for the process optimal control. A comparison of simulation results in the presence of disturbances is presented, where the resulting temperature trajectories exhibit similar tendencies as industrial data.






This work is licensed under a Creative Commons Attribution 4.0 International License.

Keywords

aerobic solid substrate fermentation; optimal temperature trajectory; steepest descent gradient; gradient projection; selective substrate

Hrčak ID:

179836

URI

https://hrcak.srce.hr/179836

Publication date:

13.4.2017.

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