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Real-time optimization of fed-batch bioreactors via adaptive extremum-seeking control

机译:通过自适应极值控制实时优化分批补料生物反应器

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摘要

This paper is concerned with the real-time optimization of fed-batch bioreactors with Haldane kinetics.The proposed adaptive extremum seeking approach utilizes the structure information of the process inetics to erive a seeking algorithm that drives the system states to the desired set-points that maximize the biomass production.Lyapunov's stability theorem is used in the design of the extremum seeking controller structure and the development of the parameter learning laws.The performance of the approach is illustrated via numerical simulations.
机译:本文涉及利用Haldane动力学对补料分批生物反应器进行实时优化的方法。所提出的自适应极值搜寻方法利用过程动力学的结构信息来推导将系统状态驱动至所需设定点的搜寻算法。利用Lyapunov稳定性定理设计极值控制器结构并建立参数学习定律,并通过数值模拟说明了该方法的性能。

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