用模糊控制器控制棕榈油厂废水暗发酵生物反应器的温度和pH值

IF 0.6 Q3 ENGINEERING, MULTIDISCIPLINARY
Ikhmal Zariq Al Imran Jamal Ikhsan, N. Abd. Rahman, J. Mohd Ali
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引用次数: 0

摘要

氢气是可再生燃料的主要选择,因为它与其他传统燃料相比具有显着的优势,例如使用废基材,更清洁,能量密度最高。生物制氢路线具有成本效益,因为它可以在环境条件下进行处理,操作技术简单,同时保持环境安全。暗发酵生产生物氢在近几十年来受到了研究人员的广泛关注,特别是由于暗发酵不需要光源。本研究是利用模糊逻辑控制器对棕榈油厂废水(POME)暗发酵生物反应器生产Bio-H2的工艺条件,特别是pH和温度进行优化研究。仿真从生物反应器的工艺流程及仪表图(P&ID)开始。然后利用MATLAB SIMULINK对传统PID控制器和模糊逻辑控制器进行了仿真,并从安全性方面对结果进行了比较。温度37℃,pH 6是产氢2.79 mol H2 mol-1葡萄糖的最佳条件。通过PID控制器和模糊控制器,pH值分别在600s和30s时达到最优值。温度控制也是如此,参数分别在200s和0.3s达到最优值。基于这些有希望的结果,模糊控制器是传统控制系统的一个很好的替代品,因为它需要更短的时间来优化过程条件,从而确保安全方面得到很好的保证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Temperature and pH Control of Dark Fermentation Bioreactor to Produce Biohydrogen from Palm Oil Mill Effluent by Using Fuzzy Logic Controller
Hydrogen is the main choice of renewable fuel since it brings significant benefits compared with the other conventional fuels, such as the use of waste substrate, cleaner and highest energy density. Biological hydrogen production route is cost efficient since it can be processed in ambient conditions, easy operational techniques while keeping the environment safe. Dark fermentation to produce bio-hydrogen has received widespread attention from researchers in the present decades especially due to not requires light sources. This work is a study of the optimization of process conditions particularly pH and temperature of a dark fermentation bioreactor to produce Bio-H2 from palm oil mill effluent (POME) by using fuzzy logic controller. The simulation started by developing process and instrumentation diagram (P&ID) of bioreactor. Then a conventional PID controller and fuzzy logic controller were simulated by using MATLAB SIMULINK and the results were compared with each other in terms of safety aspect. The temperature of 37oC and pH of 6 is the optimum conditions that needs to be maintained to yield the hydrogen at 2.79 mol H2 mol-1 glucose. The pH is able to reach optimum value at 600s and 30s by using the PID controller and fuzzy logic controller, respectively. Same goes to temperature control, where the parameter reaches optimum value at 200s and 0.3s respectively. Based on these promising results, fuzzy logic controller is a good replacement for the conventional control systems since it requires shorter time to optimize process conditions, consequently making sure the safety aspect is well guaranteed.
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来源期刊
Jurnal Kejuruteraan
Jurnal Kejuruteraan ENGINEERING, MULTIDISCIPLINARY-
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