2735. Deployment of Sustainable and Efficient Lunar Mining Systems Under Uncertainty: A Distributionally Robust Model Predictive Control Approach
Invited abstract in session WB-39: Sustainable Supply Chains I, stream Sustainable & Resilient Systems and Infrastructures.
Wednesday, 10:30-12:00Room: Newlyn LG.01
Authors (first author is the speaker)
| 1. | Kosuke Ikeya
|
| 2. | Michel-Alexandre Cardin
|
| Design Engineering, Imperial College London | |
| 3. | Jan Cilliers
|
| Imperial College London | |
| 4. | Stanley Starr
|
| Imperial College London, Department of Earth Science and Engineering | |
| 5. | Kathryn Hadler
|
| Luxembourg Institute of Science and Technology, European Space Resources Innovation Centre | |
| 6. | Antonio del Rio Chanona
|
| Imperial College London |
Abstract
To establish long-lasting and sustainable complex engineering systems, some crucial factors in the future, such as changes in demand, need to be considered and incorporated into their designs, deployment, and operations. However, predicting the long-term future over decades, is extremely difficult. To address this challenge, there is an increasing need to develop tools to support decision-makers in optimizing the designs, deployment, and operations of engineering systems under deep uncertainty. Past studies have proposed methods considering a range of uncertain parameters or subsets of plausible values. However, these new methodologies are often complex and require multiple-step implementation. As an alternative and conceptually simpler approach to tackle deep uncertainty, this project employs distributionally robust multi-objective model predictive control (MPC) to solve a sequential decision problem. MPC has been used in various industries, such as chemical processing, for its usefulness. The proposed method considers a set of distributions for uncertain parameters and optimizes sequential decisions given the current state. As a case study, the proposed method is applied to optimize the deployment of an oxygen mining plant on the Moon to minimize the embodied energy and maximize sustainability, considering the lunar oxygen demand uncertainty. The effectiveness of the method is compared with two conventional approaches, the decision rule approach and robust decision-making.
Keywords
- Strategic Planning and Management
- Optimal Control
- Decision Analysis
Status: accepted
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