A Modified Mutation-Dissipation Binary Particle Swarm Optimization Algorithm and Its Application to WFGD Control

被引:0
作者
Li, Hongxing [1 ]
Wang, Ling [1 ,2 ]
Wang, Ling [1 ,2 ]
Zhen, LanLan [2 ,3 ]
Zhen, LanLan [2 ,3 ]
Huang, Ziyuan [3 ]
机构
[1] Bao Steel Co, Shanghai Bao Steel Power Plant, Shanghai, Peoples R China
[2] Shanghai Univ, Sch Mechatron & Automat, Shanghai 200041, Peoples R China
[3] Shanghai Univ Elect Power, Informat & Control Dept, Shanghai 200041, Peoples R China
来源
ISISE 2008: INTERNATIONAL SYMPOSIUM ON INFORMATION SCIENCE AND ENGINEERING, VOL 2 | 2008年
关键词
PSO; mutation; PID; dissipation operator;
D O I
10.1109/ISISE.2008.191
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The absorber slurry pH value control is very important in the limestone-gypsum wet flues gas desulphurization technology which is widely adopted in thermal power plant in China. As the simple PID control method can not get the satisfactory control performance because of the complexity of the absorber slurry pH value control, we propose a modified mutation-dissipation binary Particle Swarm Optimization (MDBPSO) algorithm and adopt it to optimize the PID controller parameters. The simulation results show MDBPSO algorithm have better optimization ability and can find the global optima effectively. By construct the proper fitness function of PID controller parameter optimization, MDBPSO algorithm can effectively find the optimal PID parameters, which make controller restrain the overshoot, quick response the change of pH value and achieve the ideal control performance of absorber slurry pH value.
引用
收藏
页码:258 / +
页数:2
相关论文
共 50 条
  • [22] A fuzzy particle swarm optimization algorithm and its application to hotspot events in spatial analysis
    Di Martino, Ferdinando
    Sessa, Salvatore
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2013, 4 (01) : 85 - 97
  • [23] Application of an improving particle swarm optimization algorithm in controller parameters optimization
    Zhao Guo-rong
    Qu Jun-wu
    Gao Qing-wei
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE INFORMATION COMPUTING AND AUTOMATION, VOLS 1-3, 2008, : 247 - +
  • [24] On a hybrid particle swarm optimization method and its application in mechanism design
    Lee, Chun-Te
    Lee, Chun-Che
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2014, 228 (15) : 2844 - 2857
  • [25] Optimization of water distribution networks using a modified particle swarm optimization algorithm
    Surco, Douglas F.
    Vecchi, Thelma P. B.
    Ravagnani, Mauro A. S. S.
    WATER SCIENCE AND TECHNOLOGY-WATER SUPPLY, 2018, 18 (02): : 660 - 678
  • [26] Application of Particle Swarm Algorithm to Optimization of PID Neural Network
    Yuan, Chi
    2011 AASRI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INDUSTRY APPLICATION (AASRI-AIIA 2011), VOL 2, 2011, : 182 - 184
  • [27] A modified particle swarm optimization algorithm for support vector machine training
    Yuan, Hejin
    Zhang, Yanning
    Zhang, Dengfu
    Yang, Gen
    WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 4128 - +
  • [28] A Modified Particle Swarm Optimization Algorithm for Community Detection in Complex Networks
    Abdollahpouri, Alireza
    Rahimi, Shadi
    Majd, Shahnaz Mohammadi
    Salavati, Chiman
    MACHINE LEARNING AND KNOWLEDGE EXTRACTION, CD-MAKE 2018, 2018, 11015 : 11 - 27
  • [29] The Kalman Particle Swarm Optimization Algorithm and its application in soft-sensor of acrylonitrile yield
    Guo, W
    Chen, GC
    Yu, JS
    PROCEEDINGS OF THE 2005 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS AND BRAIN, VOLS 1-3, 2005, : 124 - 127
  • [30] Modified particle swarm optimization algorithm by enhancing search ability of global optimal particle
    Zhang Wei
    Shi Yibing
    Ma Dong
    Liu Guozhen
    PROCEEDINGS OF 2015 IEEE 12TH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS (ICEMI), VOL. 1, 2015, : 456 - 462