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Safety-Critical Traffic Control by Connected Automated Vehicles
Connected automated vehicles (CAVs) have shown great potential in improving traffic throughput and stability.
Machine Learning Accelerated PDE Backstepping Observers
State estimation is important for a variety of tasks, from forecasting to substituting for unmeasured states in feedback controllers.
Modular Transfer Learning with Transition Mismatch Compensation for Excessive Disturbance Rejection
In this paper, we propose a transfer learning framework that adapts a control policy for excessive disturbance rejection of an underwater robot under dynamics model mismatch.
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