5 papers · 1 filter
Physics-Informed Learning of Feedback-Linearizing Representations
Pavlos Kallinikidis, Fengjun Yang, David Snyder +4
Feedback linearization is a powerful tool in nonlinear control, but finding the linearizing coordinate transform remains challenging. Feedback linearizing transforms are governed b…
Distributionally Robust Imitation Learning: Layered Control Architecture for Certifiable Autonomy
Aditya Gahlawat, Ahmed Aboudonia, Sandeep Banik +5
Imitation learning (IL) enables autonomous behavior by learning from expert demonstrations. While more sample-efficient than comparative alternatives like reinforcement learning, I…
Scalable Distributed Nonlinear Control Under Flatness-Preserving Coupling
Fengjun Yang, Jake Welde, Nikolai Matni
We study distributed control for a network of nonlinear, differentially flat subsystems subject to dynamic coupling. Although differential flatness simplifies planning and control…
Learning Flatness-Preserving Residuals for Pure-Feedback Systems
Fengjun Yang, Jake Welde, Nikolai Matni
We study residual dynamics learning for differentially flat systems, where a nominal model is augmented with a learned correction term from data. A key challenge is that generic re…
Coordinating Planning and Tracking in Layered Control Policies via Actor-Critic Learning
Fengjun Yang, Nikolai Matni
We propose a reinforcement learning (RL)-based algorithm to jointly train (1) a trajectory planner and (2) a tracking controller in a layered control architecture. Our algorithm ar…