An integrated output space partition and optimal control method of multiple-model for nonlinear systems

被引:6
|
作者
Song, Chunyue [1 ]
Wu, Bing [1 ,2 ]
Zhao, Jun [1 ]
Xu, Zuhua [1 ]
机构
[1] Zhejiang Univ, Coll Control Sci & Engn, Inst Ind Proc Control, Hangzhou 310027, Zhejiang, Peoples R China
[2] Qingdao Univ Sci & Technol, Qingdao 266042, Peoples R China
关键词
Nonlinear systems; Output-space partition; Optimal control; Multilinear model; Hybrid systems; DYNAMIC MATRIX CONTROL; PREDICTIVE CONTROL; ADAPTIVE-CONTROL; MULTIMODEL; STABILITY;
D O I
10.1016/j.compchemeng.2018.02.018
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A systematic method for optimally partitioning operating range of each linear subsystem in output space under the criterion of closed-loop performance is initiated, when a multiple model approach is applied to nonlinear systems. As a result, an integrated output space partition and optimal control method is proposed. Firstly, linear input-output models are identified at given operating points and then reformulated as a hybrid model underlying each state having the same physical meaning. Secondly, the optimal state space partition is obtained according to a closed-loop control index. Finally, based on the obtained optimal state space partition, an optimal output space partition is achieved with the projection technique. Furthermore, a hybrid model-MPC strategy is designed according to the obtained multiple-model associated with its optimal output space partition. The integrated output space partition and optimal control method can improve the nonlinear system overall control performance and results of numerical simulation are provided. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:32 / 43
页数:12
相关论文
共 50 条
  • [1] An integrated state space partition and optimal control method of multi-model for nonlinear systems based on hybrid systems
    Song, Chunyue
    Wu, Bing
    Zhao, Jun
    Li, Ping
    JOURNAL OF PROCESS CONTROL, 2015, 25 : 59 - 69
  • [2] An Integrated State Space Partition and Optimal Control Method of Multi-model for Nonlinear Systems with State Estimation
    Xia, Bingwei
    Song, Chunyue
    Wu, Bing
    2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 1604 - 1609
  • [3] Adaptive Multiple-Model Control of A Class of Nonlinear Systems
    Yang, Chao
    Jia, Yingmin
    JOURNAL OF ROBOTICS NETWORKING AND ARTIFICIAL LIFE, 2015, 2 (02): : 69 - 72
  • [4] Adaptive Multiple-Model Control of A Class of Nonlinear Systems
    Yang, Chao
    Jia, Yingmin
    PROCEEDINGS OF INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS (ICAROB2015), 2015, : 245 - 248
  • [5] Observer-based multiple-model adaptive output feedback control for a class of nonlinear systems
    Chen, Jie
    Chen, Wei
    Sun, Jian
    TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2014, 36 (07) : 884 - 890
  • [6] Non-fragile multiple-model switching control for nonlinear systems
    Qian, Chengshan
    Hu, Chengzhong
    Jiang, Changsheng
    Wang, Yanqing
    2007 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6, 2007, : 31 - +
  • [7] A PWA model identification method based on optimal operating region partition with the output-error minimization for nonlinear systems
    Song, Chunyue
    Wang, Jiaorao
    Ma, Xinda
    Zhao, Jun
    JOURNAL OF PROCESS CONTROL, 2020, 88 : 1 - 9
  • [8] MULTIPLE-MODEL DESIGN AND SWITCHING SOLUTION FOR NONLINEAR PROCESSES CONTROL
    Lupu, Ciprian
    Popescu, Dumitru
    Petrescu, Catalin
    Ticlea, Alexandru
    Irimia, Bogdan
    Dimon, Catalin
    Udrea, Andreea
    6TH INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE 2008, 2008, : 71 - 76
  • [9] Multiple-model adaptive explicit predictive control for nonlinear MIMO system
    Dutta, Lakshmi
    Das, Dushmanta Kumar
    JOURNAL OF CONTROL AND DECISION, 2024,
  • [10] Event-Triggered Multiple-Model Identifier for a Class of Nonlinear Systems
    Ugarakhod, Rashmi
    Tripathi, Shikha
    George, Koshy
    JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS, 2023, 34 (05) : 971 - 984