Data-driven distributionally robust MPC for systems with uncertain dynamics
Author:
Affiliation:
1. ETH Zürich,Automatic Control Laboratory,the Department of Information Technology and Electrical Engineering,Switzerland
2. University of Texas at Dallas,Department of Mechanical Engineering,USA
Funder
European Research Council
United States Air Force
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9992315/9992317/09992469.pdf?arnumber=9992469
Reference23 articles.
1. Constrained model predictive control: Stability and optimality
2. Robust model predictive control using tubes
3. Recursively feasible Robust MPC for linear systems with additive and multiplicative uncertainty using optimized polytopic dynamics
4. Probabilistic Constrained MPC for Multiplicative and Additive Stochastic Uncertainty
5. Stochastic Tubes in Model Predictive Control With Probabilistic Constraints
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1. Wasserstein Distributionally Robust Control of Partially Observable Linear Stochastic Systems;IEEE Transactions on Automatic Control;2024-09
2. Data-Driven Distributionally Robust Mitigation of Risk of Cascading Failures;2024 American Control Conference (ACC);2024-07-10
3. Wasserstein Tube MPC with Exact Uncertainty Propagation;2023 62nd IEEE Conference on Decision and Control (CDC);2023-12-13
4. Distributionally Robust Differential Dynamic Programming With Wasserstein Distance;IEEE Control Systems Letters;2023
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