Design of fuzzy controller based on particle swarm optimization algorithm and its application in flue gas denitration

LU Chenxu; GAO Haidong; GAO Lin; GAO Yaokui; LYU Haitao; LI Hua

doi:10.19666/j.rlfd.202110218

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Design of fuzzy controller based on particle swarm optimization algorithm and its application in flue gas denitration

更新时间：2025-09-28

- Design of fuzzy controller based on particle swarm optimization algorithm and its application in flue gas denitration
- Thermal Power Generation Vol. 51, Issue 4, Pages: 188-193(2022)
- 作者机构：
  
  1. 西安热工研究院有限公司
  2. 华能秦煤瑞金发电有限责任公司
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202110218
  CLC： TP273.4;TP18;X701
- Published：2022
- 稿件说明：
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LU Chenxu, GAO Haidong, GAO Lin, et al. Design of fuzzy controller based on particle swarm optimization algorithm and its application in flue gas denitration[J]. Thermal power generation, 2022, 51(4): 188-193.
DOI：

LU Chenxu, GAO Haidong, GAO Lin, et al. Design of fuzzy controller based on particle swarm optimization algorithm and its application in flue gas denitration[J]. Thermal power generation, 2022, 51(4): 188-193. DOI： 10.19666/j.rlfd.202110218.

摘要

针对模糊控制器设计难度大、推广困难的问题，提出一种利用粒子群（PSO）算法设计模糊控制器的方法。通过将二维模糊控制器的模糊推理过程理解为二元函数，将控制器设计问题转变为函数曲面寻优问题，避免了设计隶属度函数、模糊规则等复杂的过程。利用网格化方法，将寻优对象降维为二维矩阵，然后采用PSO算法寻找最适合被控对象的函数曲面，从而完成模糊控制器的设计。以火电厂选择性催化还原（SCR）烟气脱硝系统为试验对象，利用此方法设计模糊PID控制器，并通过与常规PID控制对比，验证了该设计方法的有效性。

Abstract

Aiming at solving the problem of large difficulty in fuzzy controller design and promotion

a method of designing fuzzy controller using particle swarm optimization(PSO) algorithm is proposed. By understanding the fuzzy reasoning process of a two-dimensional fuzzy controller as a binary function

the controller design problem is transformed into a function surface optimization problem

which avoids the complicated process of designing membership functions and fuzzy rules. By using the meshing method

the dimensionality of the optimization object is reduced to a two-dimensional matrix

and then the PSO algorithm is used to find the most suitable function surface for the controlled object

thereby completing the design of the fuzzy controller. By taking the selective catalytic reduction(SCR) flue gas denitrification system of thermal power unit as the experimental object

this method is applied to design a fuzzy PID controller

and the effectiveness of this design method is verified through comparison with the conventional PID control.

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