Quality Monitoring for the Basic OxygenFurnace Steelmaking Process based on Nonlinear Filter

This paper addresses on the quality (the carbon content and the temperature of molten steel) monitoring problem for the basic oxygen furnace (BOF) steelmaking process. It can be realized by designing the filter for the system of BOF steelmaking process, which can be attributed to a class of discrete-time nonlinear systems with time delay and persistent bounded disturbances. To solve the design problem of nonlinear filter, the conditions of one-sided Lipschitz and quadratic inner-boundedness are introduced. The purpose of design is to efficiently attenuate the peak of estimation error caused by the disturbances. In order to solve the state estimation problem of the general system (the state transition matrix is stable) and the BOF steelmaking-like system (the state transition matrix is an identity one), Schur Complements and Finsler’s Lemma are introduced in the theoretical analysis, respectively. The algorithm stability and the sufficient conditions are derived to ensure the given performance, and the parameters of the filter algorithms are the solutions of linear matrix inequality (LMI). And the validity of the developed methods are verified by numerical examples, one of which is the BOF steelmaking numerical example, and the related results also have reference value for the actual production.