Title :
Non-linear State Estimation for Continuous Stirred Tank Reactor using Neural Network State Filter
Author :
Srinivasan, K. ; Prakash, Jayavel
Author_Institution :
Dept. of Instrum. Eng., Anna Univ., Chennai
Abstract :
In this paper, a systematic approach to design a non-linear observer to estimate the state vector of a non-linear dynamic system has been presented. The neural network based state filtering algorithm proposed by A.G. Parlos et al. has been used by the authors to estimate the state variables, concentration and temperature in the CSTR process
Keywords :
Kalman filters; chemical reactors; continuous systems; neural nets; nonlinear control systems; nonlinear dynamical systems; nonlinear estimation; observers; state estimation; temperature; CSTR; concentration; continuous stirred tank reactor; neural network state filter; nonlinear dynamic system; nonlinear observer; nonlinear state estimation; state filtering algorithm; state vector estimation; temperature; Continuous-stirred tank reactor; Filtering algorithms; Filters; Mathematical model; Neural networks; Nonlinear dynamical systems; Observers; Sampling methods; State estimation; Temperature; CSTR; Kalman Filter; Neural Network;
Conference_Titel :
India Conference, 2006 Annual IEEE
Conference_Location :
New Delhi
Print_ISBN :
1-4244-0369-3
Electronic_ISBN :
1-4244-0370-7
DOI :
10.1109/INDCON.2006.302760
