Advanced control algorithms embedded in a programmable logic controller

被引:12
作者
Gerksic, Sarno [1 ]
Dolanc, Gregor
Vrancic, Damir
Kocijan, Jus
Strmcnik, Stanko
Blazic, Saso
Skrjanc, Igor
Marinsek, Zoran
Bozicek, Miha
Stathaki, Anna
King, Robert
Hadjiski, Mincho
Boshnakov, Kosta
机构
[1] Jozef Stefan Inst, Ljubljana, Slovenia
[2] Nova Gorica Polytech, Nova Gorica, Slovenia
[3] Univ Ljubljana, Fac Elect Engn, Ljubljana, Slovenia
[4] INEA doo, Ljubljana, Slovenia
[5] Inst Comp Technol, Athens, Greece
[6] Univ Chem Technol & Met Sofia, Sofia, Bulgaria
关键词
control engineering; fuzzy modelling; industrial control; model-based control; nonlinear control; programmable logic controllers; self-tuning regulators;
D O I
10.1016/j.conengprac.2005.05.006
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents an innovative self-tuning nonlinear controller ASPECT (advanced control algorithms for programmable logic controllers). It is intended for the control of highly nonlinear processes whose properties change radically over its range of operation, and includes three advanced control algorithms. It is designed using the concepts of agent-based systems, applied with the aim of automating some of the configuration tasks. The process is represented by a set of low-order local linear models whose parameters are identified using an online learning procedure. This procedure combines model identification with pre- and post-identification steps to provide reliable operation. The controller monitors and evaluates the control performance of the closed-loop system. The controller was implemented on a programmable logic controller (PLC). The performance is illustrated on a field test application for control of pressure on a hydraulic valve. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:935 / 948
页数:14
相关论文
共 21 条
[1]   Fuzzy self-tuning PI control of pH in fermentation [J].
Babuska, R ;
Oosterhoff, J ;
Oudshoorn, A ;
Bruijn, PM .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2002, 15 (01) :3-15
[2]   NONLINEAR CONTROL OF CHEMICAL PROCESSES - A REVIEW [J].
BEQUETTE, BW .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 1991, 30 (07) :1391-1413
[3]  
Blazic S, 2003, 2003 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS 1 AND 2, PROCEEDINGS, P912
[4]   A practical multiple model adaptive strategy for multivariable model predictive control [J].
Dougherty, D ;
Cooper, D .
CONTROL ENGINEERING PRACTICE, 2003, 11 (06) :649-664
[5]   Multiple model adaptive control design for a multiple-input multiple-output chemical reactor [J].
Gundala, R ;
Hoo, KA ;
Piovoso, MJ .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2000, 39 (06) :1554-1564
[6]   Supervision of adaptive control algorithms [J].
Hägglund, T ;
Åström, KJ .
AUTOMATICA, 2000, 36 (08) :1171-1180
[7]  
Henson M., 1997, Nonlinear Process Control
[8]   Adaptive nonlinear control of a pH neutralization process [J].
Henson, Michael A. ;
Seborg, Dale E. .
IEEE Transactions on Control Systems Technology, 1994, 2 (03) :169-182
[9]  
KARBA R, 1999, PROCESS MODELLING
[10]  
Kocijan J, 2003, 2003 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS 1 AND 2, PROCEEDINGS, P906