Modeling and Control of Level Control Process- A Comparative Study

被引：0

作者：

Nair, Aiswarya Lakshmi Sasidharan ^{[1
]}

Mary, S. Anitha Janet ^{[1
]}

Linsely, J. Arul ^{[1
]}

机构：

[1] Noorul Islam Ctr Higher Educ, Dept Elect & Elect, Kanyakumari, India

来源：

2017 INNOVATIONS IN POWER AND ADVANCED COMPUTING TECHNOLOGIES (I-PACT) | 2017年

关键词：

flow rates; interacting systems; level control systems; SISO systems; non -interacting systems; MATLAB;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Tank level control systems are everywhere. All of our process industries mostly depends on this tank level control systems. This paper deals with the modeling and control of a two tank liquid level control system. The considered non linear system is a Single Input Single Output (SISO) system. The goal of the level control is to track the desired level of liquid in to the second tank by controlling the flow rate of the first tank. The tanks are coupled in the interacting and non-interacting ways and a comparison is made between these two systems. The mathematical modeling is done by mass balance method and the PID controller is designed by the trial and error method. The system is simulated with both open loop and closed loop conditions. A comparative study of the time domain response of the two systems while using the PID controller is done by the MATLAB simulation.

引用

页数：4

共 50 条

[1] Modeling of control loop in production sheduling and inventory level control process
Gjeldum, Nikola
Tufekcic, Dzemo
Veza, Ivica
ANNALS OF DAAAM FOR 2007 & PROCEEDINGS OF THE 18TH INTERNATIONAL DAAAM SYMPOSIUM: INTELLIGENT MANUFACTURING & AUTOMATION: FOCUS ON CREATIVITY, RESPONSIBILITY, AND ETHICS OF ENGINEERS, 2007, : 297 - 298
[2] Comparative Analysis of Different Controller for a Nonlinear Level Control Process
Kala, H.
Aravind, P.
Valluvan, M.
2013 IEEE CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES (ICT 2013), 2013, : 724 - 729
[3] Process structure-based recurrent neural network modeling for predictive control: A comparative study
Alhajeri, Mohammed S.
Luo, Junwei
Wu, Zhe
Albalawi, Fahad
Christofides, Panagiotis D.
CHEMICAL ENGINEERING RESEARCH & DESIGN, 2022, 179 : 77 - 89
[4] Modeling closed kinematic chains for control: A comparative study
Wang, Zhiyong
Ghorbel, Fathi H.
PROCEEDINGS OF THE ASME DYNAMIC SYSTEMS AND CONTROL DIVISION 2005, PTS A AND B, 2005, : 1507 - 1513
[5] Modeling for Liquid-Level Control System in Beer Fermentation Process
Bi Shujiao
Dong Feng
PROCEEDINGS OF THE 31ST CHINESE CONTROL CONFERENCE, 2012, : 1739 - 1744
[6] Study on modeling and intelligent control of wort evaporating process
Hou, DB
Zhou, ZK
PROCEEDINGS OF 2005 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-9, 2005, : 2443 - 2447
[7] The Study on Modeling and Control of Double Carbonylation Reaction Process
Zhang, Shi
Ding, Feng
Jiang, Nan
2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, : 4745 - +
[8] Modeling and control of the TMP process
Chang, G
Schwartz, HM
Phung, T
CONTROL SYSTEMS '96, PREPRINTS, 1996, : 117 - 123
[9] PROCESS MODELING FOR INTELLIGENT CONTROL
FERAYBEAUMONT, S
COREA, R
THAM, MT
MORRIS, AJ
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 1992, 5 (06) : 483 - 492
[10] Modeling to Optimize Process Control
Richards, Marty
Schmotzer, Richard
Pogal, Gail E.
2001, Chemical Week Associates (108):

← 1 2 3 4 5 →