Safe Nonlinear Control Under Control Constraints via Reachability, Optimal Control and Reinforcement Learning
Autonomous robots in the real world have nonlinear dynamics with actuators that are subject to constraints. The combination of the two poses complicates the task of designing stabilizing controllers that can guarantee safety, which we denote as the stabilize-avoid problem. Existing control-based tec...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2024
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| Online Access: | https://hdl.handle.net/1721.1/155344 |