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A Dynamic Firefly Algorithm-Based Fractional Order Fuzzy-PID Approach for the Control of a Heavy-Duty Gas Turbine

机译:一种基于动态萤火虫算法的分数阶模糊PID方法,用于控制重型燃气轮机

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Heavy duty gas turbines have long played an important role in energy production. Advanced turbine designs are expected to be highly efficient, able to quickly ramp the output power up and down and promptly tolerate loading variations without breaching emissions regulations. Control design plays an important role in ensuring high efficiency and performance of gas turbines. This paper proposes a fractional order fuzzy-PID approach for a heavy-duty gas turbine. The controller gains are optimized using a Firefly algorithm enhanced with a dynamic parameter selection. This latter is used to speed up the convergence rate of the Firefly algorithm, optimize the gains of the fractional order fuzzy-PID and enhance the performance and efficiency of the gas turbine. The proposed approach is implemented to the speed loop of a gas turbine in order to maintain the output temperature and the turbine’s speed within their desired values during either a sudden change in loading or a drop in frequency. A comparison analysis with a standard Firefly algorithm-based approach was carried out to further assess the performance of the proposed evolved firefly algorithm-based approach.
机译:重型燃气轮机长期以来在能源生产中发挥着重要作用。先进的涡轮机设计预计将高效,能够快速上下速度上下斜坡,并及时容忍加载变化而不违反排放法规。控制设计在确保燃气轮机的高效率和性能方面发挥着重要作用。本文提出了一种重型燃气轮机的分数秩序模糊PID方法。使用动态参数选择,使用萤火虫算法进行优化控制器增益。后者用于加速萤火虫算法的收敛速率,优化分数阶模糊PID的增益,提高燃气轮机的性能和效率。所提出的方法用于燃气轮机的速度环,以便在突然变化或频率下降的突然变化期间将输出温度和涡轮机的速度保持在其所需值内。采用标准萤火虫算法的方法进行了比较分析,以进一步评估所提出的发展萤火虫算法的方法的性能。

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