Title :
Estimation of component concentrations of sodium aluminate solution via PLS and Hammerstein recurrent neural networks
Author :
Wang, Wei ; Zhao, Lijie ; Chai, Tianyou ; Yu, Wen
Author_Institution :
Key Lab. of Integrated Autom. of Process Ind., Northeastern Univ., Shenyang, China
Abstract :
In this paper, a new on-line soft sensing method is proposed for component concentrations of sodium aluminate solution. With this sensing strategy, real-time control and optimization can be realized in aluminate production plants. Several advance techniques are used, such as PLS (Partial Least Squares), Hammerstein model, recurrent neural networks and least square algorithm. Industrial experiment results show that the proposed soft sensing algorithm is effective.
Keywords :
Internet; chemistry computing; least squares approximations; recurrent neural nets; Hammerstein recurrent neural network; PLS; aluminate production plant; component concentration estimation; online soft sensing method; partial least square algorithm; real-time control; sodium aluminate solution; Artificial neural networks; Computational modeling; Data models; Heuristic algorithms; Nonlinear dynamical systems; Recurrent neural networks; Temperature measurement;
Conference_Titel :
Advanced Computational Intelligence (IWACI), 2010 Third International Workshop on
Conference_Location :
Suzhou, Jiangsu
Print_ISBN :
978-1-4244-6334-3
DOI :
10.1109/IWACI.2010.5585154
