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The fractional PID controllers tuned by genetic algorithms for expansion turbine in the cryogenic air separation process

机译:遗传算法调整的比例PID控制器在低温空分过程中膨胀涡轮机的应用

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This paper deals with the design of a new algorithm of PID control based on fractional calculus (FC) in production of technical gases, i.e. in a cryogenic air separation process. Production of low pressure liquid air was first introduced by P. L. Kapica and involved expansion in a gas turbine. For application in the synthesis of the control law, for the input temperature and flow of air to the expansion turbine, it is necessary to determine the appropriate differential equations of the cryogenic process of mixing of two gaseous airflows at different temperatures before entrance to the expansion turbine. Thereafter, the model is linearized and decoupled and consequently classical PID and fractional order controllers are taken to assess the quality of the proposed technique. A set of optimal parameters of these controllers are achieved through the genetic algorithm optimization procedure by minimizing a cost function. Our design method focuses on minimizing performance criterion which involves IAE, overshoot, as well as settling time. A time-domain simulation was used to identify the performance of controller with respect to a traditional optimized PID controller. [Projekat Ministarstva nauke Republike Srbije, br. 35006]
机译:本文研究了一种基于分数演算(FC)的PID控制新算法的设计,该算法用于工业气体(即低温空气分离过程)的生产中。低压液态空气的生产首先由P. L. Kapica引入,涉及在燃气轮机中进行膨胀。为了在控制定律的综合中应用,对于膨胀机的输入温度和空气流量,有必要在进入膨胀机之前确定不同温度下两种气流混合的低温过程的适当微分方程。涡轮。此后,模型被线性化和解耦,因此采用经典的PID和分数阶控制器来评估所提出技术的质量。通过最小化成本函数,通过遗传算法优化过程可实现这些控制器的一组最佳参数。我们的设计方法着重于最小化涉及IAE,超调和建立时间的性能标准。相对于传统的优化PID控制器,使用时域仿真来确定控制器的性能。 [Projekat Ministarstva nauke Republike Srbije,br。 35006]

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