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Study on optimization control Method of Bed temperature for Circulating Fluidized Bed

机译:循环流化床床温优化控制方法研究

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The combustion system of Circulating Fluidized Bed (CFB) boiler is a strong-coupled non-linear system with large delay. Bed temperature is one of the most important parameters, which influences the safety of unit and couples with the main steam pressure strongly. A reliable control method is beneficial to suppress the temperature fluctuation. In this paper, a fuzzy PI controller based on Genetic Algorithm (GA) is designed for the model of bed temperature, of which the parameters are optimal in the region to ensure the control effect. On the basis of mechanism analysis and gray correlation analysis, a multivariable model is built. The coal feed and the primary air are selected as inputs, the bed temperature and main steam pressure are selected as outputs. Then the model is decoupled by partial feed-forward method, and the GA is used to optimize the parameters of the fuzzy PI controller. Simulations are carried out in different conditions and the results indicate that the performance of optimized fuzzy PI controller based on proposed model is better than fuzzy PI controller.
机译:循环流化床(CFB)锅炉的燃烧系统是具有大延迟的强耦合的非线性系统。床温是最重要的参数之一,它影响了单位和耦合的安全性强烈。可靠的控制方法有利于抑制温度波动。在本文中,设计了一种基于遗传算法(GA)的模糊PI控制器,用于床温模型,其中参数在该区域中最佳,以确保控制效果。在机制分析和灰色相关分析的基础上,建立了一种多变量模型。选择煤炭饲料和初级空气作为输入,选择床温和主蒸汽压力作为输出。然后,该模型通过部分前馈方法解耦,并且GA用于优化模糊PI控制器的参数。在不同的条件下进行仿真,结果表明,基于所提出的模型的优化模糊PI控制器的性能优于模糊PI控制器。

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