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Design and Tuning of Standard Additive Model Based Fuzzy PID Controllers for Multivariable Process Systems

机译:基于标准加性模型的多变量过程系统模糊PID控制器的设计与优化

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This paper describes a design and two-level tuning method for fuzzy proportional-integral derivative (FPID) controllers for a multivariable process where the fuzzy inference uses the inference of standard additive model. The proposed method can be used for any $n times n$ multiinput–multioutput process and guarantees closed-loop stability. In the two-level tuning scheme, the tuning follows two steps: low-level tuning followed by high-level tuning. The low-level tuning adjusts apparent linear gains, whereas the high-level tuning changes the nonlinearity in the normalized fuzzy output. In this paper, two types of FPID configurations are considered, and their performances are evaluated by using a real-time multizone temperature control problem having a 3 $times$ 3 process system.
机译:本文描述了一种模糊多比例积分微分(FPID)控制器的设计和两级调整方法,用于多变量过程,其中模糊推理使用标准加性模型的推理。所提出的方法可用于任何n次乘以n次的多输入多输出过程,并保证闭环稳定性。在两级调优方案中,调优遵循两个步骤:低级调优,然后是高级调优。低电平调整可调整视在线性增益,而高层调整可更改归一化模糊输出中的非线性。在本文中,考虑了两种类型的FPID配置,并通过使用具有3 x 3的过程系统的实时多区域温度控制问题评估了它们的性能。

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