基于LSSA优化的火电机组脱硫系统PID-GPC复合控制研究

何佳玮; 康英伟

doi:10.19805/j.cnki.jcspe.2025.240439

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基于LSSA优化的火电机组脱硫系统PID-GPC复合控制研究

数字化与智能化 | 更新时间：2026-10-10

- 基于LSSA优化的火电机组脱硫系统PID-GPC复合控制研究
- Study on PID-GPC Composite Control of Desulfurization System in Thermal Power Plant Based on LSSA Optimization
- 动力工程学报 2025年45卷第9期页码：1492-1501
- 作者机构：
  
  上海电力大学自动化工程学院,上海,200090
- 作者简介：
  
  何佳玮(1999—),男,上海人,硕士研究生,研究方向为先进发电过程的建模、仿真与控制
  康英伟(通信作者),男,副教授,博士,E-mail:controlkyw@126.com
- 基金信息：
  
  国家自然科学基金资助项目(61573239);上海发电过程智能管控工程技术研究中心资助项目(14DZ2251100)
- DOI：10.19805/j.cnki.jcspe.2025.240439
  中图分类号：
- 网络首发：2025-09-16，
  
  纸质出版：2025
- 稿件说明：
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何佳玮,康英伟. 基于LSSA优化的火电机组脱硫系统PID-GPC复合控制研究动力工程学报, 2025, 45(9): 1492-1501 https://doi.

org/10.19805/j.cnki.jcspe.2025.240439
何佳玮,康英伟. 基于LSSA优化的火电机组脱硫系统PID-GPC复合控制研究动力工程学报, 2025, 45(9): 1492-1501 https://doi. DOI： 10.19805/j.cnki.jcspe.2025.240439.

org/10.19805/j.cnki.jcspe.2025.240439 DOI：

摘要

为提高燃煤火力发电厂石灰石-石膏湿法脱硫效率

同时保证电厂工作运行的稳定

提出一种基于比例-积分-微分(proportional-integral-derivative

PID)与广义预测控制(generalized predictive control

GPC)加权的复合控制方案

以确保电厂脱硫塔浆液pH值和出口SO

质量浓度处于理想值

从而实现合理的脱硫控制目标。其中

脱硫系统模型参数、PID参数、PID-GPC复合控制权重因子均利用改进麻雀搜索算法(logistic sparrow search algorithm

LSSA)进行寻优。仿真结果表明:辨识模型能作为GPC的预测模型;复合控制算法融合了PID与GPC的优点

系统的响应特性得到提升;LSSA优化后的复合控制动态性能得到提升

抗干扰能力明显增强

同时能够有效跟踪设定目标。

Abstract

To improve the efficiency of limestone-gypsum wet flue gas desulfurization in coal-fired power plants while ensuring stable operation

a weighted composite control scheme based on proportional-integral-derivative (PID) and generalized predictive control (GPC) was proposed for maintaining the pH value of the desulfurization tower slurry and the outlet SO

mass concentration at ideal levels

thereby achieving a reasonable desulfurization control target. The desulfurization system model parameters

PID parameters

and the weight factors of the PID-GPC composite control were all optimized using an improved logistic sparrow search algorithm (LSSA). Simulation results ind

icate that the identified model can serve as the prediction model for GPC; the composite control algorithm integrates the advantages of both PID and GPC

enhancing the system's response characteristics; and the composite control optimized by LSSA exhibits improved dynamic performance

significantly enhances anti-interference capability

and effectively tracks the set targets.

关键词

Keywords

references

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