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首页> 外文期刊>Journal of Cleaner Production >Performance and robustness evaluation of Nonlinear Autoregressive with Exogenous input Model Predictive Control in controlling industrial fermentation process
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Performance and robustness evaluation of Nonlinear Autoregressive with Exogenous input Model Predictive Control in controlling industrial fermentation process

机译:非线性自回归与外源输入模型预测控制在工业发酵过程中的性能和鲁棒性评估

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Malaysia holds a variety of energy resources; oil, natural gas, coal and renewable energies such as biomass, solar and hydro. In spite of these abundant resources, the nation still reliant on fossil fuel for industrial and transportation sector even though fossil fuel is depleting worldwide. In this regard, renewable energy resources are becoming attractive for sustainable energy development in Malaysia. Bioethanol is one of a potential biofuel with a high octane number and has replaced lead as an octane enhancer in petrol. In bioethanol fermentation, the process possesses complex dynamics caused by the microorganisms involved in the process as well as the variation in the biomass composition with the operating conditions. In this work, a nonlinear model known as the Nonlinear Autoregressive with Exogenous input model was developed and embedded in the Model Predictive Control strategy to control the fermentation process. Then, the performance of the Nonlinear Autoregressive with Exogenous input Model Predictive Control was evaluated and compared with linear Model Predictive Control and Proportional Integral Derivative controller for set point tracking and disturbance rejections. The robustness tests have also been carried out using the linear and nonlinear Model Predictive Controls proposed. In the robustness test, the nonlinear Model Predictive Controller successfully settled back to the original product concentration and fermenter temperature set points with settling time three hours. Meanwhile the linear Model Predictive Controller only settled at 95.8% of the product concentration set point and 97.1% of the fermenter temperature set point with settling time more than five hours. From the results, Nonlinear Autoregressive with Exogenous input Model Predictive Control has shown better performance and more robust as compared to linear Model Predictive Control and Proportional Integral Derivative controller. (C) 2016 Elsevier Ltd. All rights reserved.
机译:马来西亚拥有多种能源;石油,天然气,煤炭和可再生能源,例如生物质能,太阳能和水能。尽管有这些丰富的资源,但即使全球范围内的化石燃料正在消耗,该国仍然依靠化石燃料来工业和交通运输。在这方面,可再生能源资源对于马来西亚的可持续能源发展越来越有吸引力。生物乙醇是具有高辛烷值的潜在生物燃料之一,并已取代铅作为汽油中的辛烷值增强剂。在生物乙醇发酵中,该过程具有复杂的动力学过程,该过程由过程中涉及的微生物引起,并且生物量组成随操作条件而变化。在这项工作中,开发了一个称为外源输入模型的非线性自回归非线性模型,并将其嵌入到模型预测控制策略中以控制发酵过程。然后,评估了带有外源输入模型预测控制的非线性自回归的性能,并将其与线性模型预测控制和比例积分微分控制器进行了设定点跟踪和干扰抑制比较。还使用提出的线性和非线性模型预测控制进行了鲁棒性测试。在稳健性测试中,非线性模型预测控制器在三个小时的建立时间内成功地回到了原始产品浓度和发酵罐温度设定点。同时,线性模型预测控制器仅在产物浓度设定点的95.8%和发酵罐温度设定点的97.1%处稳定,稳定时间超过5小时。从结果来看,与线性模型预测控制和比例积分微分控制器相比,带有外源输入模型预测控制的非线性自回归已显示出更好的性能和更强的鲁棒性。 (C)2016 Elsevier Ltd.保留所有权利。

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