Design of Dual Loop Networked Control Systems with Different Sampling Rate Based on Gain Adaptive Smith Predictor

被引:0
作者
Zhao, Hong [1 ]
Che, Ke [1 ]
机构
[1] Guilin Univ Technol, Coll Mech & Control Engn, Guilin 541004, Peoples R China
来源
ISBDAI '18: PROCEEDINGS OF THE INTERNATIONAL SYMPOSIUM ON BIG DATA AND ARTIFICIAL INTELLIGENCE | 2018年
关键词
Different sampling rate; Dual loop networked control systems; Smith predictor; Gain adaptive;
D O I
10.1145/3305275.3305333
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A class of dual loop networked control systems with different sampling rate is discussed in this paper. Generally, Smith predictor can be used to overcome the influence of network delay. However, influence of prediction model inaccuracy, different sampling rate and interference always appear in the actual systems, and the systems based on conventional Smith predictor cannot achieve the desired control effect. The gain adaptive Smith predictor is proposed for this class of networked control systems, which can be used to overcome the problems caused by inaccurate prediction model, interference and various sampling rate. The simulation results based on MATLAB show that the proposed method is efficient and feasible.
引用
收藏
页码:290 / 293
页数:4
相关论文
共 9 条
[1]  
Gu Chengcheng, 2013, MANUFACTURING AUTOMA, V12, P36
[2]  
Hong Zhao, 2018, 3 INT C CONTR AUT AR
[3]  
Jun Zhang, 2012, J HARBIN U TECHNOLOG, V17, P34
[4]  
Keyou You, 2013, AUTOMATION J, V39, P111
[5]  
Li Jian-yong, 2015, Journal of Zhengzhou University Engineering Science, V36, P6, DOI 10.3969/j.issn.1671-6833.2015.04.002
[6]  
Takchung Y Fu, 2012, ENG APPL ARTIF INTEL, V24, P164
[7]  
Wang Ruifeng, 2015, Computer Engineering and Applications, V51, P113, DOI 10.3778/j.issn.1002-8331.1311-0057
[8]   The Study of Fuzzy-PI Control in Supercritical Unit Main Steam Temperature [J].
Wang Wen-lan ;
Xi Dong-min .
2012 FIFTH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID 2012), VOL 2, 2012, :3-5
[9]  
Yao H., 2018, ACTA INFORM MALAYSIA, V2, P07