Handling state constraints and economics in feedback control of transport-reaction processes

• Computationally efficient EMPC of nonlinear parabolic PDEs with state and control constraints.
• Improved economic performance and constraint handling via time-varying operation.
• Extensive computational studies elucidating the impact of controller parameters on performance.

Transport-reaction processes, which are typically described by parabolic partial differential equations (PDEs), play an important role within the chemical process industries. Therefore, it is important to develop feedback control techniques that operate transport-reaction processes in an economically optimal fashion in the presence of constraints in the process states and manipulated inputs. Economic model predictive control (EMPC) is a predictive control scheme that combines process economics and feedback control into an integrated framework with the potential of improving the closed-loop process economic performance compared to traditional control methodologies. In this work, we focus on systems of nonlinear parabolic PDEs and propose a novel EMPC design integrating adaptive proper orthogonal decomposition (APOD) method with a high-order finite-difference method to handle state constraints. The computational efficiency and constraint handling properties of this design are evaluated using a tubular reactor example modeled by two nonlinear parabolic PDEs.