ժҪ The knowledge of transient temperature of the ladle wall is a key factor in optimizing energy consumption in steelmaking process. The transient temperature needs to be estimated. A nonlinear lumped parameter model was used to model the thermal dynamics of the ladle. Then, the bounded Jacobian nonlinear observer was utilized to estimate the temperature. With this method, the estimation model became a closed-loop model and the observer gains were obtained by solving linear matrix inequalities and simply implemented to the system. Comparison between the simulation and recorded data at a participating steel plant in Thailand showed that the nonlinear observer accurately estimated the temperature of the ladle lining. This estimated temperature was very useful in determining suitable tapping temperature for energy conservation and steel quality.
Abstract��The knowledge of transient temperature of the ladle wall is a key factor in optimizing energy consumption in steelmaking process. The transient temperature needs to be estimated. A nonlinear lumped parameter model was used to model the thermal dynamics of the ladle. Then, the bounded Jacobian nonlinear observer was utilized to estimate the temperature. With this method, the estimation model became a closed-loop model and the observer gains were obtained by solving linear matrix inequalities and simply implemented to the system. Comparison between the simulation and recorded data at a participating steel plant in Thailand showed that the nonlinear observer accurately estimated the temperature of the ladle lining. This estimated temperature was very useful in determining suitable tapping temperature for energy conservation and steel quality.
G. PHANOMCHOENG,S. CHANTRANUWATHANA,P. CHARUNYAKORN. On-line Ladle Lining Temperature Estimation by Using Bounded Jacobian Nonlinear Observer[J]. �й������ڿ���, 2016, 23(8): 792-799.
G. PHANOMCHOENG,S. CHANTRANUWATHANA,P. CHARUNYAKORN. On-line Ladle Lining Temperature Estimation by Using Bounded Jacobian Nonlinear Observer. Chinese Journal of Iron and Steel, 2016, 23(8): 792-799.
2016, Vol. 23 
