论文信息 - Applications of non-linear filtering to the stainless-steel decarbonization process

Applications of non-linear filtering to the stainless-steel decarbonization process

Abstract An extended Kalman filter is applied to a stainless-steel manufacturing operation in order to estimate the molten metal composition in real time. A recently developed process model forms the basis of the filter. The performance of the estimator is tested for several levels of measurement information and for both continuous and discrete samples. The results indicate that reliable estimates of the metal bath composition can be obtained even when only bath temperature can be measured.

W. H. Ray | J. Szekely | M. A. Soliman

[1] D. A. Wismer,et al. Advances in Process Control Applications , 1971 .

[2] Henry Cox,et al. On the estimation of state variables and parameters for noisy dynamic systems , 1964 .

[3] R. E. Kalman,et al. New Results in Linear Filtering and Prediction Theory , 1961 .

[4] A. Jazwinski. Stochastic Processes and Filtering Theory , 1970 .

[5] R. E. Kalman,et al. A New Approach to Linear Filtering and Prediction Problems , 2002 .