Hybrid Model Based Optimal Control for a Metallurgy Process

This paper applies hybrid modeling method based optimal control in industrial process. Hybrid modeling method combines a priori information with a nonlinear residual compensation technique to build a global model which predicts alumina raw pulp slurry quality. Process control is accomplished based on blending expert knowledge with multi-objective hierarchy reasoning approach. Through the coordination of model and controller, the optimal control of blending process is achieved. Application results show that the proposed method can resolve optimization problems of a kind of industrial processes characterized by time delay and multi-constraints.