Design of switching multilinear model predictive control using gap metric

Park, Byung Jun; Kim, Yeonsoo; Lee, Jong Min

doi:10.1016/j.compchemeng.2021.107317

Cited by 8 publications

(2 citation statements)

References 29 publications

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“…In standard or regular MPC, control action is calculated by solving an online optimization problem at each time step. The computational burden of the controller is increased due to the complex structure of QP, resulting in a delayed response time . Furthermore, including constraints and variable interactions into the control algorithm (QP) results in a slower response.…”

Section: Introductionmentioning

confidence: 99%

“…The computational burden of the controller is increased due to the complex structure of QP, resulting in a delayed response time. 21 Furthermore, including constraints and variable interactions into the control algorithm (QP) results in a slower response. Alternatively, the computational burden of the MPC controller can be reduced by solving the QP fragmentally into small fractions and accelerating calculation time in control action utilizing online optimization called the Fast MPC approach.…”

Section: Introductionmentioning

confidence: 99%

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Model Analysis for the Implementation of a Fast Model Predictive Control Scheme on the Absorption/Stripping CO₂ Capture Plants

et al. 2022

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The purpose of this paper is to investigate the possible implementation of the Fast model predictive control (MPC) scheme for chemical systems. Due to the difficulties associated with complicated dynamic behavior and model sensitivity, which results in considerable offsets, the Fast MPC controller has not been implemented on the CO 2 capture plant based on the absorption/stripping system. The main objective of this work is to evaluate the most appropriate model for implementing the Fast MPC control strategy, which results in fast output responses, negligible offsets, and minimum errors. The steady-state and dynamic simulation models of the CO 2 capture plant are designed in Aspen PLUS. In the System Identification Toolbox, multiple state-space models are identified to achieve a highly accurate model for the Fast MPC controller. The Fast MPC controller is then implemented to evaluate the performance under a setpoint tracking mode with ±5 and ±15% step changes. The results showed that the Fast MPC based on the statespace prediction focus model has on average 7.9 times lower offset than the simulation focus model and 10.4 times lower integral absolute error values. The comparison study concluded that the Fast MPC control strategy performs efficiently using prediction-based focus state-space models for CO 2 capture plants using the absorption/stripping system with minimum offsets and errors.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Model Analysis for the Implementation of a Fast Model Predictive Control Scheme on the Absorption/Stripping CO₂ Capture Plants

et al. 2022

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Piecewise Smooth Hybrid System Identification for Model Predictive Control

Stolyarov

Sandoval

Petsagkourakis

et al. 2022

Computer Aided Chemical Engineering

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Flexible operation of the pressurized water reactor nuclear power system using multi-model predictive control over a wide nonlinear operating range

Cui

Zhang

et al. 2023

Applied Thermal Engineering

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Design of switching multilinear model predictive control using gap metric

Cited by 8 publications

References 29 publications

Model Analysis for the Implementation of a Fast Model Predictive Control Scheme on the Absorption/Stripping CO₂ Capture Plants

Model Analysis for the Implementation of a Fast Model Predictive Control Scheme on the Absorption/Stripping CO₂ Capture Plants

Piecewise Smooth Hybrid System Identification for Model Predictive Control

Flexible operation of the pressurized water reactor nuclear power system using multi-model predictive control over a wide nonlinear operating range

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Design of switching multilinear model predictive control using gap metric

Cited by 8 publications

References 29 publications

Model Analysis for the Implementation of a Fast Model Predictive Control Scheme on the Absorption/Stripping CO2 Capture Plants

Model Analysis for the Implementation of a Fast Model Predictive Control Scheme on the Absorption/Stripping CO2 Capture Plants

Piecewise Smooth Hybrid System Identification for Model Predictive Control

Flexible operation of the pressurized water reactor nuclear power system using multi-model predictive control over a wide nonlinear operating range

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Model Analysis for the Implementation of a Fast Model Predictive Control Scheme on the Absorption/Stripping CO₂ Capture Plants

Model Analysis for the Implementation of a Fast Model Predictive Control Scheme on the Absorption/Stripping CO₂ Capture Plants