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    Practical algorithm for stochastic optimal control problem about microbial fermentation in batch culture

    Access Status
    Fulltext not available
    Authors
    Wang, L.
    Yuan, J.
    Wu, Changzhi
    Wang, X.
    Date
    2017
    Type
    Journal Article
    
    Metadata
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    Citation
    Wang, L. and Yuan, J. and Wu, C. and Wang, X. 2017. Practical algorithm for stochastic optimal control problem about microbial fermentation in batch culture. Optimization Letters. 13 (3): pp. 527-541.
    Source Title
    Optimization Letters
    DOI
    10.1007/s11590-017-1220-z
    ISSN
    1862-4472
    School
    Department of Construction Management
    URI
    http://hdl.handle.net/20.500.11937/59573
    Collection
    • Curtin Research Publications
    Abstract

    How to add glycerol to maximize production of 1,3-propanediol (1,3-PD) is a critical problem in process control of microbial fermentation. Most of the existing works are focusing on modelling this process through deterministic-based differential equations. However, this process is not deterministic, but intrinsically stochastic considering nature of interference. Thus, it is of importance to consider stochastic microorganism. In this paper, we will modelling this process through stochastic differential equations and maximizing production of 1,3-PD is formulated as an optimal control problem subject to continuous state constraints and stochastic disturbances. A modified particle swarm algorithm through integrating the hybrid Monte Carlo sampling and path integral is proposed to solve this problem. The constraint transcription, local smoothing and time-scaling transformation are introduced to handle the continuous state constraints. Numerical results show that, by employing the obtained optimal control governed by stochastic dynamical system, 1,3-PD concentration at the terminal time can be increased compared with the previous results.

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