Nonlinear Offset-Free Model Predictive Control based on Dynamic PLS Framework

被引：0
|
作者：
Zhao, Qiang [1 ]
Jin, Xin [1 ]
Yu, Huapeng [1 ]
Lu, Shan [2 ]
机构：
[1] Liaoning Petrochem Univ, Sch Informat & Control Engn, Fushun 113001, Peoples R China
[2] Shenzhen Polytech, Inst Intelligence Sci & Engn, Shenzhen 518055, Peoples R China
来源：
PROCESSES | 2021年 / 9卷 / 10期
基金：
中国国家自然科学基金;
关键词：
partial least square; model predictive control; nonlinear system; offset-free control; PARTIAL LEAST-SQUARES; EFFICIENCY;
D O I：
10.3390/pr9101784
中图分类号：
TQ [化学工业];
学科分类号：
0817 ;
摘要：
A nonlinear offset-free model predictive control based on a dynamic partial least square (PLS) framework is proposed in this paper. A multi-output multi-input system is projected into latent variable space by a PLS outer model. For each latent variable model, the T-S fuzzy model is used to describe the nonlinear characteristics of the system; while the state-space model is used in T-S fuzzy model consequent parameters to describe the dynamic characteristics. A disturbance model is introduced in the state-space model. For model state variables, a state observer is used to compensate for the mismatch of the model. The case study results for the pH neutralization process show that the MPC controller based on this method can guarantee the tracking performance of the nonlinear system without static error.</p>
引用
收藏
页数：16
相关论文
共 50 条
  • [1] Linear Offset-Free Model Predictive Control in the Dynamic PLS Framework
    Hou, Ligang
    Wu, Ze
    Jin, Xin
    Wang, Yue
    [J]. INFORMATION, 2019, 10 (01):
  • [2] Offset-Free Nonlinear Model Predictive Control
    Tatjewski, Piotr
    [J]. TRENDS IN ADVANCED INTELLIGENT CONTROL, OPTIMIZATION AND AUTOMATION, 2017, 577 : 33 - 44
  • [3] Nonlinear offset-free model predictive control
    Morari, M.
    Maeder, U.
    [J]. AUTOMATICA, 2012, 48 (09) : 2059 - 2067
  • [4] Lyapunov-Based Offset-free Model Predictive Control of Nonlinear Systems
    Das, Buddhadeva
    Mhaskar, Prashant
    [J]. 2014 AMERICAN CONTROL CONFERENCE (ACC), 2014, : 2839 - 2844
  • [5] Integration of offset-free control framework with Koopman Lyapunov-based model predictive control
    Son, Sang Hwan
    Narasingam, Abhinav
    Kwon, Joseph Sang-Il
    [J]. 2021 AMERICAN CONTROL CONFERENCE (ACC), 2021, : 2818 - 2823
  • [6] Integrated approach to AUV docking based on nonlinear offset-free model predictive control
    Shi, Kai
    Wang, Xiaohui
    Xu, Huixi
    Chen, Zhong
    Zhao, Hongyin
    [J]. MEASUREMENT & CONTROL, 2023, 56 (3-4): : 733 - 750
  • [7] Offset-free Nonlinear Model Predictive Control by the Example of Maglev Vehicles
    Schmid, Patrick
    Eberhard, Peter
    [J]. IFAC PAPERSONLINE, 2021, 54 (06): : 83 - 90
  • [8] LYAPUNOV-BASED OFFSET-FREE MODEL PREDICTIVE CONTROL OF NONLINEAR PROCESS SYSTEMS
    Das, Buddhadeva
    Mhaskar, Prashant
    [J]. CANADIAN JOURNAL OF CHEMICAL ENGINEERING, 2015, 93 (03): : 471 - 478
  • [9] Fast Offset-Free Nonlinear Model Predictive Control Based on Moving Horizon Estimation
    Huang, Rui
    Biegler, Lorenz T.
    Patwardhan, Sachin C.
    [J]. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2010, 49 (17) : 7882 - 7890
  • [10] UKF Based Nonlinear Offset-free Model Predictive Control for Ship Dynamic Positioning Under Stochastic Disturbances
    Deng, Fang
    Yang, Hua-Lin
    Wang, Long-Jin
    Yang, Wei-Min
    [J]. INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2019, 17 (12) : 3079 - 3090
12345