子空间拓扑
高炉
控制理论(社会学)
过程(计算)
双线性插值
控制器(灌溉)
鉴定(生物学)
非线性系统
最优控制
跟踪(教育)
工程类
控制工程
计算机科学
数学优化
控制(管理)
数学
冶金
材料科学
人工智能
教育学
植物
量子力学
物理
计算机视觉
心理学
生物
农学
操作系统
摘要
Summary Blast 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.
科研通智能强力驱动
Strongly Powered by AbleSci AI