STATE ESTIMATION OF A NONLINEAR SYSTEM USING PARTICLE FILTER

被引:0
作者
Anandhakumar, K. [1 ]
Ali, I. Syed Meer Kulam [1 ]
Selvakumar, K. [2 ]
Raja, K. [3 ]
机构
[1] EBET Grp Inst, Dept EEE, Tirupur 638108, India
[2] SRM Univ, Dept EEE, Madras 603203, Tamil Nadu, India
[3] Knowledge Inst Technol, Dept EEE, Salem 637504, India
来源
2014 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (IEEE ICCIC) | 2014年
关键词
State Estimation; CSTR; Process Industries; Particle Filter; Nonlinear system;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, Particle Filter algorithm has been employed for estimating the states namely concentration and temperature of a Continuous Stirred Tank Reactor (CSTR) and simulation results are presented. The propagation of particles through the nonlinear system model for the state estimation has been discussed. The states of the system are estimated by using the Particle Filter algorithm under the steady state as well as transient system conditions. A step change in the coolant flow rate has been introduced in order to provide a dynamic operating point.
引用
收藏
页码:805 / 808
页数:4
相关论文
共 15 条
[1]  
[Anonymous], 2006, IEEE INT C IND TECHN, DOI DOI 10.1109/ICIT.2006.372687
[2]  
[Anonymous], IEEE ANN C
[3]  
Banu US, 2006, INDIA INTERNATIONAL CONFERENCE ON POWER ELECTRONIC S, P371, DOI 10.1109/IICPE.2006.4685400
[4]  
Bequette B.W., 2003, PROCESS CONTROL MODE
[5]   MMSE-Based Filtering in Presence of Non-Gaussian System and Measurement Noise [J].
Bilik, Igal ;
Tabrikian, Joseph .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2010, 46 (03) :1153-1170
[6]   An overview of existing methods and recent advances in sequential Monte Carlo [J].
Cappe, Olivier ;
Godsill, Simon J. ;
Moulines, Eric .
PROCEEDINGS OF THE IEEE, 2007, 95 (05) :899-924
[7]   Particle filters for state estimation of jump Markov linear systems [J].
Doucet, A ;
Gordon, NJ ;
Krishnamurthy, V .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2001, 49 (03) :613-624
[8]   NOVEL-APPROACH TO NONLINEAR NON-GAUSSIAN BAYESIAN STATE ESTIMATION [J].
GORDON, NJ ;
SALMOND, DJ ;
SMITH, AFM .
IEE PROCEEDINGS-F RADAR AND SIGNAL PROCESSING, 1993, 140 (02) :107-113
[9]  
Khodabandeh M., 2007, 2007 International Conference on Control, Automation and Systems - ICCAS '07, P1466, DOI 10.1109/ICCAS.2007.4406570
[10]  
Li Kim-Hung, STATISTICASINICA, V17, P895