Design and implementation of constrained predictive control simplified algorithm based on particle swarm optimization

被引:0
|
作者
Wang, Kai-Chen [1 ]
Ma, Ping [1 ]
机构
[1] North China Elect Power Univ, Dept Automat, Baoding 071003, Hebei, Peoples R China
关键词
constrained predictive control; Dynamic Matrix Control; particle swarm optimization; algorithm simplification;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In order to achieve the purpose of reducing the calculation quantity and improving the computation speed of predictive control, an aggregation algorithm was proposed to design the predictive control simplified algorithm. At the same time, consider the actuators' outputs with restrictions in industrial, the particle swarm optimization was used to design the output constraint on the basis of predictive control simplified algorithm. Finally, the algorithm was applied to boiler denitration control system by PLC in a power plant in Shaanxi Province. The practical result shows that the predictive control algorithm also can be implemented in the device with limited hardware resources and has a good control effect.
引用
收藏
页码:685 / 690
页数:6
相关论文
共 50 条
  • [1] Constrained Fuzzy Predictive Control Using Particle Swarm Optimization
    Sahed, Oussama Ait
    Kara, Kamel
    Hadjili, Mohamed Laid
    APPLIED COMPUTATIONAL INTELLIGENCE AND SOFT COMPUTING, 2015, 2015
  • [2] Simplified particle swarm optimization algorithm
    Martins, Carlos Humberto
    Barbosa dos Santos, Ricardo Paupitz
    Santos, Febio Lucio
    ACTA SCIENTIARUM-TECHNOLOGY, 2012, 34 (01) : 21 - 25
  • [3] Particle Swarm Optimization and Alienor method to constrained multivariable Predictive control
    Ali, Thamallah
    Anis, Sakly
    Faouzi, M'Sahli
    2016 17TH INTERNATIONAL CONFERENCE ON SCIENCES AND TECHNIQUES OF AUTOMATIC CONTROL AND COMPUTER ENGINEERING (STA'2016), 2016, : 61 - 66
  • [4] Adaptive Switching Control Algorithm Design based on Particle Swarm optimization
    Wang Lili
    Xin Ling
    PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021), 2021, : 7373 - 7378
  • [5] An Improved Particle Swarm Algorithm Based on Cultural Algorithm for Constrained Optimization
    Wang, Lina
    Cao, Cuiwen
    Xu, Zhenhao
    Gu, Xingsheng
    KNOWLEDGE DISCOVERY AND DATA MINING, 2012, 135 : 453 - 460
  • [6] Constrained optimization by the ε constrained hybrid algorithm of particle swarm optimization and genetic algorithm
    Takahama, T
    Sakai, S
    Iwane, N
    AI 2005: ADVANCES IN ARTIFICIAL INTELLIGENCE, 2005, 3809 : 389 - 400
  • [7] Constrained optimization with an improved particle swarm optimization algorithm
    Munoz Zavala, Angel E.
    Hernandez Aguirre, Arturo
    Villa Diharce, Enrique R.
    Botello Rionda, Salvador
    INTERNATIONAL JOURNAL OF INTELLIGENT COMPUTING AND CYBERNETICS, 2008, 1 (03) : 425 - 453
  • [8] Particle swarm optimization algorithm for constrained problems
    Zhang, Jian-Ming
    Xie, Lei
    ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, 2009, 4 (04) : 437 - 442
  • [9] Constrained reentry trajectory optimization based on improved particle swarm optimization algorithm
    Xu Tianyun
    Zhou Jun
    Guo Jianguo
    Lu Qing
    SEVENTH SYMPOSIUM ON NOVEL PHOTOELECTRONIC DETECTION TECHNOLOGY AND APPLICATIONS, 2021, 11763
  • [10] Simplified Particle Swarm Optimization Algorithm Based on Improved Learning Factors
    Gao, Wei
    Song, Chuyi
    Jiang, Jingqing
    Zhang, Chenggang
    ADVANCES IN NEURAL NETWORKS, PT I, 2017, 10261 : 321 - 328