Data-driven distributionally robust iterative risk-constrained model predictive control
Author:
Affiliation:
1. Engineering and Technology Institute Groningen, University of Groningen
Funder
University of Groningen
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9837955/9837961/09838319.pdf?arnumber=9838319
Reference18 articles.
1. Risk-Aware Motion Planning and Control Using CVaR-Constrained Optimization
2. Risk-sensitive motion planning using entropic value-at-risk;dixit;ArXiv Preprint,2020
3. Wasserstein Distributionally Robust Motion Planning and Control with Safety Constraints Using Conditional Value-at-Risk
4. Distributionally robust risk map for learning-based motion planning and control: A semidefinite programming approach;hakobyan;ArXiv Preprint,2021
5. Learning to Satisfy Unknown Constraints in Iterative MPC
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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. Wasserstein Distributionally Robust Risk-Constrained Iterative MPC for Motion Planning: Computationally Efficient Approximations;2023 62nd IEEE Conference on Decision and Control (CDC);2023-12-13
5. Distributionally Robust Optimization with Unscented Transform for Learning-Based Motion Control in Dynamic Environments;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29
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