Nowadays, real-time optimization (RTO) and nonlinear as well as linear model predictive control (MPC) are standard methods in operation and process control systems. Hence there exists a good understanding of how to combine RTO and set point tracking MPC schemes. However, recently, there has been substantial progress in analyzing the properties of so-called economic MPC schemes. This paper proposes a conceptual framework to blend ideas from (output) modifier adaptation and offset-free economic MPC with recent results on economic MPC without terminal constraints. Specifically, we leverage recent insights into economic MPC based on turnpike and dissipativity properties of the underlying optimal control problem. Interestingly, the proposed scheme alleviates the need for a dedicated computation of steady-state targets by exploiting the turnpike property in the open-loop predictions. Two detailed simulation examples show that the proposed schemes deliver excellent performance, while being conceptually much simpler.

Toward a Unifying Framework Blending Real-Time Optimization and Economic Model Predictive Control

Pannocchia G.
2019-01-01

Abstract

Nowadays, real-time optimization (RTO) and nonlinear as well as linear model predictive control (MPC) are standard methods in operation and process control systems. Hence there exists a good understanding of how to combine RTO and set point tracking MPC schemes. However, recently, there has been substantial progress in analyzing the properties of so-called economic MPC schemes. This paper proposes a conceptual framework to blend ideas from (output) modifier adaptation and offset-free economic MPC with recent results on economic MPC without terminal constraints. Specifically, we leverage recent insights into economic MPC based on turnpike and dissipativity properties of the underlying optimal control problem. Interestingly, the proposed scheme alleviates the need for a dedicated computation of steady-state targets by exploiting the turnpike property in the open-loop predictions. Two detailed simulation examples show that the proposed schemes deliver excellent performance, while being conceptually much simpler.
2019
Faulwasser, T.; Pannocchia, G.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/995193
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