Optimized PI Control with Tracking Differentiator for Negative Pressure Cabin Control

H. Ren, Cui-Cui Song
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Abstract

To block the epidemics like "Corona Virus Disease 2019(COVID-19)" spreading, an effective isolation of the infected patients during the transportation is an important issue, which makes the negative pressure cabin (NPC) become a key equipment. There exist some practical NPCs in service, whose pressures are mostly controlled using the conventional PID controller with parameters regulated by engineering methods. Until now, there is no report about the model of NPC system from the authors’ best knowledge. In this paper, the model of the NPC system is reported, which is an inherent nonlinear system. Because of the nonlinear nature of the cabin pressure, the conventional PID controller cannot achieve desire performance to balance the transient and the steady state performance, even though the optimized PID parameters are chosen using the on-line optimization based on genetic algorithm. To solve such a problem, Tracking Differentiator (TD) and PI controller are combined to achieve the desire performance using the optimized parameters. The experiment results show the improvement of the proposed method.
带跟踪微分器的优化PI控制负压座舱控制
为了阻断“2019冠状病毒病”(COVID-19)等疫情的传播,在运输过程中有效隔离感染者是一个重要问题,这使得负压舱(NPC)成为关键设备。目前在役的一些实际npc,其压力控制多采用传统的PID控制器,参数采用工程方法调节。到目前为止,据作者所知还没有关于NPC系统模型的报道。本文报道了NPC系统的模型,它是一个固有的非线性系统。由于客舱压力的非线性特性,传统的PID控制器即使采用基于遗传算法的在线优化方法选择优化后的PID参数,也无法达到平衡稳态和瞬态性能的理想效果。为了解决这一问题,将跟踪微分器(TD)与PI控制器相结合,利用优化后的参数实现理想的性能。实验结果表明了该方法的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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