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A two-stage robust-intelligent controller design for efficient LFC based on Kharitonov theorem and fuzzy logic

机译:基于Kharitonov定理和模糊逻辑的二级LFC高效LFC智能控制器设计。

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摘要

This paper proposes an efficient load frequency control (LFC) approach based on robust and intelligent methods. Practically speaking, proportional-integral (PI) controller is widely deployed in LFC structure. Basically, the parameters of PI controller are adjusted based on trial-and-error or classic control methods. In such manners, robust performance of PI controller cannot be guaranteed in disturbances including load changes or parameter variations. In this research, at the first stage, the gain values of PI controller are tuned in an offline manner based on Kharitonov theorem which strengthens the validity of the controller against the variations in time constants of turbine and governor. As another aspect of uncertainty, power system loading demand is changed ceaselessly. To accommodate such conditions, at the second stage, the initial gain values based on Kharitonov theorem are adapted in an online manner based on fuzzy logic approach. The fuzzy controller, as an aspect of intelligence, adapts the proportional and integral gains through appropriate membership functions in an online fashion. Frequency deviation and its derivative are selected as efficient input signals for the fuzzy controller. Detailed numerical studies are conducted to assess performance of the proposed approach. Results demonstrate a reliable frequency performance against different uncertainties.
机译:本文提出了一种基于鲁棒和智能方法的有效负载频率控制(LFC)方法。实际上,比例积分(PI)控制器广泛应用于LFC结构中。基本上,PI控制器的参数是基于反复试验或经典控制方法进行调整的。以这种方式,在包括负载变化或参数变化在内的干扰中不能保证PI控制器的鲁棒性能。在本研究中,在第一阶段,基于Kharitonov定理以离线方式对PI控制器的增益值进行了调整,从而增强了针对涡轮机和调速器时间常数变化的控制器的有效性。作为不确定性的另一方面,电力系统的负载需求不断变化。为了适应这样的条件,在第二阶段,基于模糊逻辑方法以在线方式调整基于Kharitonov定理的初始增益值。作为智能的一个方面,模糊控制器通过适当的隶属函数以在线方式调整比例和积分增益。选择频率偏差及其导数作为模糊控制器的有效输入信号。进行了详细的数值研究,以评估该方法的性能。结果证明了针对不同不确定性的可靠频率性能。

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