Optimal tracking control for blast furnace molten iron quality based on subspace identification and Krotov's method

Abstract

SummaryBlast furnace ironmaking is a complex nonlinear dynamic process, which has strict requirements on the quality of final molten iron. To improve the control effect of molten iron quality, this paper proposes an optimal tracking control method for molten iron quality based on the bilinear subspace identification and Krotov's method. First, a state space model between key process variables and blast furnace molten iron quality, using the bilinear subspace identification method, is established based on actual industrial data. Then, an augmented system is established combining the state vector and the reference trajectory, and the improving feedback controller is designed by solving a set of Riccati equations, which are established based on Krotov's method. In combination with the designed controller and the established system, the specific implementation steps are proposed. Finally, the effectiveness and advancement of the proposed method are verified based on actual industrial data of a large blast furnace.

The Meaning and Accuracy of the Improving Functions in the Solution of the CBQR by Krotov’s Method

“…It is a well-known instrument for constructing optimal control for quantum systems [12,13]. Additionally, its efficiency was demonstrated for a class of structural control problems [14][15][16], iron and steel manufacturing processes [17], and biological systems [18].…”