Constrained applied predictive control based on closed-loop subspace identification

Abstract

In order to deal with constrained characteristics in the closed-loop industrial processes, a constrained applied predictive control(CAPC) method based on closed-loop subspace identification is proposed. The state-space model is obtained through the closed-loop subspace identification algorithm, which is regarded as the system model. Then, the model is used to design the model predictive controller which involves the solution of a quadratic program solving constraints. The paper presents a comparison of performance given by proposed control method when applied to a 2-CSTR system with an open-loop subspace CAPC method, the superiority of the proposed method is illustrated through the simulation results.