Model-free Adaptive Control for a Vapour-Compression Refrigeration Benchmark Process

被引:11
作者
Yu, Xian [1 ]
Hou, Zhongsheng [1 ]
Zhang, Xin [1 ]
机构
[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Adv Control Syst Lab, Beijing 100044, Peoples R China
来源
IFAC PAPERSONLINE | 2018年 / 51卷 / 04期
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
Model free adaptive control; dynamic linearization; vapour-compression; refrigeration system; Benchmark PID 2018; SYSTEMS; LINEARIZATION;
D O I
10.1016/j.ifacol.2018.06.149
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A model-free adaptive control (MFAC) is applied to the Refrigeration Systems based on Vapour Compression of the BENCHMARK PID 2018. A SISO MFAC controller and a MIMO MFAC controller are designed to control the outlet temperature of evaporator secondary flux and the superheating degree of refrigerant at evaporator outlet by manipulating the expansion valve opening and the compressor speed. The two designed controllers are the pure data driven control methods without using any model information of the refrigeration process in the control implementation by virtue of the dynamic linearization technique, and the PID controllers can be considered as special cases of the two designed controllers. The qualitative and quantitative comparison results between the MFAC schemes and the default PID controllers given in the simulation platform provided by the Benchmark PID 2018 demonstrate the effectiveness of the two designed controllers. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码:527 / 532
页数:6
相关论文
共 21 条
  • [1] [Anonymous], 2005, THESIS
  • [2] [Anonymous], 1994, THESIS
  • [3] A novel optimization algorithm based on epsilon constraint-RBF neural network for tuning PID controller in decoupled HVAC system
    Attaran, Seyed Mohammad
    Yusof, Rubiyah
    Selamat, Hazlina
    [J]. APPLIED THERMAL ENGINEERING, 2016, 99 : 613 - 624
  • [4] Bejarano G., 2017, BENCHMARK PID 2018
  • [5] Multivariable analysis and H∞ control of a one-stage refrigeration cycle
    Bejarano, Guillermo
    Alfaya, Jose A.
    Ortega, Manuel G.
    Rubio, Francisco R.
    [J]. APPLIED THERMAL ENGINEERING, 2015, 91 : 1156 - 1167
  • [6] Campi MC, 2000, IEEE DECIS CONTR P, P623, DOI 10.1109/CDC.2000.912835
  • [7] Development of a Predictive Control Based on Takagi-Sugeno Model Applied in a Nonlinear System of Industrial Refrigeration
    Franco, I. C.
    Schmitz, J. E.
    Costa, T. V.
    Fileti, A. M. F.
    Silva, F. V.
    [J]. CHEMICAL ENGINEERING COMMUNICATIONS, 2017, 204 (01) : 39 - 54
  • [8] Iterative feedback tuning: Theory and Applications
    Hjalmarsson, H
    Gevers, M
    Gunnarsson, S
    Lequin, O
    [J]. IEEE CONTROL SYSTEMS MAGAZINE, 1998, 18 (04): : 26 - 41
  • [9] Hou Z, 2013, Model free adaptive control
  • [10] An Overview of Dynamic-Linearization-Based Data-Driven Control and Applications
    Hou, Zhongsheng
    Chi, Ronghu
    Gao, Huijun
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2017, 64 (05) : 4076 - 4090