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首页> 外文期刊>International Journal of Innovative Research in Science, Engineering and Technology >Intelligent Optimal Control of a Heat Exchanger Using ANFIS and Interval Type-2 Based Fuzzy Inference System
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Intelligent Optimal Control of a Heat Exchanger Using ANFIS and Interval Type-2 Based Fuzzy Inference System

机译:基于ANFIS和区间2型模糊推理系统的换热器智能优化控制。

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In this paper, adaptive network based fuzzy inference system (ANFIS) was used in control applications of a Heat Exchanger as interval type-2 fuzzy logic controller (IT-2FL). Two adaptive networks based fuzzy inference systems were chosen to design type-2 fuzzy logic controllers for each control applications. The whole integrated system for control of Heat Exchanger is called IT2 FLC+ANFIS controller. Membership functions in interval type-2 fuzzy logic controllers were set as an area called footprint of uncertainty (FOU), which is limited by two membership functions of adaptive network based fuzzy inference systems; they were upper membership function (UMF) and lower membership function (LMF). This work deals with the design and application of an IT2 FLC+ANFIS controller for a heat exchanger. To deal with the problem of parameter adjustment, efficient neuro-fuzzy scheme known as the ANFIS (Adaptive Network-based Fuzzy Inference System) can be used. The IT2 FLC+ANFIS controller of the heat exchanger is compared with classical PID control. System behaviors were defined by Lagrange formulation and MATLAB computer simulations. The simulation results confirm that interval type2 fuzzy is one of the possibilities for successful control of heat exchangers. The advantage of this approach is that it is not a linear-model-based strategy. Comparison of the simulation results obtained using IT2 FLC+ANFIS controller and those obtained using classical PID control demonstrates the effectiveness and superiority of the proposed approach because of the smaller consumption of the heating medium.
机译:在本文中,基于自适应网络的模糊推理系统(ANFIS)在换热器的控制应用中用作区间类型2模糊逻辑控制器(IT-2FL)。选择了两个基于自适应网络的模糊推理系统来为每种控制应用设计2型模糊逻辑控制器。整个用于热交换器控制的集成系统称为IT2 FLC + ANFIS控制器。区间类型2模糊逻辑控制器中的隶属度函数设置为一个区域,称为不确定足迹(FOU),该区域受基于自适应网络的模糊推理系统的两个隶属度函数的限制;它们是上级隶属度函数(UMF)和下级隶属度函数(LMF)。这项工作涉及用于热交换器的IT2 FLC + ANFIS控制器的设计和应用。为了解决参数调整的问题,可以使用称为ANFIS(基于自适应网络的模糊推理系统)的有效神经模糊方案。将热交换器的IT2 FLC + ANFIS控制器与经典PID控制进行了比较。系统行为由Lagrange公式和MATLAB计算机仿真定义。仿真结果证实区间2模糊是成功控制热交换器的可能性之一。这种方法的优点是它不是基于线性模型的策略。使用IT2 FLC + ANFIS控制器获得的仿真结果与使用经典PID控制获得的仿真结果的比较证明了该方法的有效性和优越性,因为加热介质的消耗量较小。

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