The predictive control (MPC) is an advanced control strategy widely used in industrial processes. MPC is also one of the most active areas of research in the theory of control. Subjects such as optimality, stability and robustness are well known, especially for linear systems. However, despite this large adoption, both in the media industry and academics, little has been written about how these drivers are implemented in practice. This article tries to fill this gap, introducing the development of systems optimization and MPC, and discussing their integration into a hierarchical control structure. The proposed integrated control scheme is applied to the Tennessee Eastman plant, and the results show the effectiveness of the proposed strategy for optimal control of processes.

The predictive control (MPC) is an advanced control strategy widely used in industrial processes. MPC is also one of the most active areas of research in the theory of control. Subjects such as optimality, stability and robustness are well known, especially for linear systems. However, despite this large adoption, both in the media industry and academics, little has been written about how these drivers are implemented in practice. This article tries to fill this gap, introducing the development of systems optimization and MPC, and discussing their integration into a hierarchical control structure. The proposed integrated control scheme is applied to the Tennessee Eastman plant, and the results show the effectiveness of the proposed strategy for optimal control of processes.