• 综合
  • 标题
  • 关键词
  • 摘要
  • 学者
  • 期刊-刊名
  • 期刊-ISSN
  • 会议名称
搜索

作者:

Han, Hong-Gui (Han, Hong-Gui.) | Wang, Yan (Wang, Yan.) | Sun, Hao-Yuan (Sun, Hao-Yuan.) | Liu, Zheng (Liu, Zheng.) | Qiao, Jun-Fei (Qiao, Jun-Fei.)

收录:

Scopus SCIE

摘要:

Model predictive control (MPC) is a practical method for addressing control issues in constrained systems. System identification and constrained optimization are two key problems that affect MPC performance. In this work, a self-organizing MPC (SOMPC) strategy is proposed for constrained nonlinear systems with unknown dynamics to achieve constraint satisfaction and improve control performance. First, the generalized multiplier method is introduced into the MPC framework to redesign the objective function. In this way, the constrained optimal control problem is reconstructed into an easily solvable unconstrained optimal problem. Second, a self-organizing fuzzy neural network (SOFNN) is adopted to identify unknown nonlinear system. Then, the performance of SOFNN is optimized by parameter updating and structure self-organization to provide accurate prediction output. Third, the gradient descent algorithm is utilized to solve nonlinear optimization problem of MPC to obtain control input. To ensure practical application, the convergence of SOFNN, the feasibility and stability of SOMPC strategy are proved. Finally, the proposed SOMPC strategy is demonstrated by a numerical experiment and an industrial process control simulation experiment, and the results show that it exhibits outstanding control performance and constraint satisfaction ability.

关键词:

Accuracy Predictive control input and output constraints Fuzzy neural network (FNN) Fuzzy neural networks Artificial neural networks Control systems Linear programming Vectors Nonlinear dynamical systems Fuzzy control model predictive control (MPC) unknown nonlinear systems (UNSs) Optimization

作者机构:

  • [ 1 ] [Han, Hong-Gui]Beijing Univ Technol, Sch Informat Sci & Technol, Beijing Key Lab Computat Intelligence & Intelligen, Beijing 100124, Peoples R China
  • [ 2 ] [Wang, Yan]Beijing Univ Technol, Sch Informat Sci & Technol, Beijing Key Lab Computat Intelligence & Intelligen, Beijing 100124, Peoples R China
  • [ 3 ] [Sun, Hao-Yuan]Beijing Univ Technol, Sch Informat Sci & Technol, Beijing Key Lab Computat Intelligence & Intelligen, Beijing 100124, Peoples R China
  • [ 4 ] [Liu, Zheng]Beijing Univ Technol, Sch Informat Sci & Technol, Beijing Key Lab Computat Intelligence & Intelligen, Beijing 100124, Peoples R China
  • [ 5 ] [Qiao, Jun-Fei]Beijing Univ Technol, Sch Informat Sci & Technol, Beijing Key Lab Computat Intelligence & Intelligen, Beijing 100124, Peoples R China

通讯作者信息:

  • [Han, Hong-Gui]Beijing Univ Technol, Sch Informat Sci & Technol, Beijing Key Lab Computat Intelligence & Intelligen, Beijing 100124, Peoples R China

查看成果更多字段

相关关键词:

相关文章:

来源 :

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS

ISSN: 2168-2216

年份: 2024

8 . 7 0 0

JCR@2022

被引次数:

WoS核心集被引频次:

SCOPUS被引频次:

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 1

归属院系:

在线人数/总访问数:482/4931315
地址:北京工业大学图书馆(北京市朝阳区平乐园100号 邮编:100124) 联系我们:010-67392185
版权所有:北京工业大学图书馆 站点建设与维护:北京爱琴海乐之技术有限公司