Deep Neural Koopman Operator-based Economic Model Predictive Control of Shipboard Carbon Capture System
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Abstract (arXiv)
Shipboard carbon capture is a promising solution to help reduce carbon emissions in international shipping. In this work, we propose a data-driven dynamic modeling and economic predictive control approach within the Koopman framework. This integrated modeling and control approach is used to achieve safe and energy-efficient process operation of shipboard post-combustion carbon capture plants. Specifically, we propose a deep neural Koopman operator modeling approach, based on which a Koopman model with time-varying model parameters is established. This Koopman model predicts the overall economic operational cost and key system outputs, based on accessible partial state measurements. By leveraging this learned model, a constrained economic predictive control scheme is developed. Despite time-varying parameters involved in the formulated model, the formulated optimization problem associated with the economic predictive control design is convex, and it can be solved efficiently during online control implementations. Extensive tests are conducted on a high-fidelity simulation environment for shipboard post-combustion carbon capture processes. Four ship operational conditions are taken into account. The results show that the proposed method significantly improves the overall economic operational performance and carbon capture rate. Additionally, the proposed method guarantees safe operation by ensuring that hard constraints on the system outputs are satisfied.
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References · 21
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9 more
- 2020On the Optimality and Convergence Properties of the Iterative Learning Model Predictive Controllercited by 2
- 2023Modeling and Control of Diesel Engine Emissions using Multi-layer Neural Networks and Economic Model Predictive Controlcited by 2
- 2024Reduced-order Koopman modeling and predictive control of nonlinear processescited by 2
- 2024Incorporating ESO into Deep Koopman Operator Modelling for Control of Autonomous Vehiclescited by 2
- 2024Efficient Economic Model Predictive Control of Water Treatment Process with Learning-based Koopman Operatorcited by 2
- 2024Machine learning-based input-augmented Koopman modeling and predictive control of nonlinear processescited by 2
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- 2024Deep Koopman Operator-Informed Safety Command Governor for Autonomous Vehiclescited by 1
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