67 citations · 190 across the 13 of their papers we have counts for
8 papers · 1 filter
Improved Sample Complexity of Imitation Learning for Barrier Model Predictive Control
Daniel Pfrommer, Swati Padmanabhan, Kwangjun Ahn +4
Recent work in imitation learning has shown that having an expert controller that is both suitably smooth and stable enables stronger guarantees on the performance of the learned c…
On the Sample Complexity of Imitation Learning for Smoothed Model Predictive Control
Daniel Pfrommer, Swati Padmanabhan, Kwangjun Ahn +4
Recent work in imitation learning has shown that having an expert controller that is both suitably smooth and stable enables stronger guarantees on the performance of the learned c…
Stabilizing Dynamical Systems via Policy Gradient Methods
Juan C. Perdomo, Jack Umenberger, Max Simchowitz
Stabilizing an unknown control system is one of the most fundamental problems in control systems engineering. In this paper, we provide a simple, model-free algorithm for stabilizi…
Distributed Identification of Contracting and/or Monotone Network Dynamics
Max Revay, Jack Umenberger, Ian R. Manchester
This paper proposes methods for identification of large-scale networked systems with guarantees that the resulting model will be contracting -- a strong form of nonlinear stability…
On the smoothness of nonlinear system identification
Antônio H. Ribeiro, Koen Tiels, Jack Umenberger +2
We shed new light on the \textit{smoothness} of optimization problems arising in prediction error parameter estimation of linear and nonlinear systems. We show that for regions of…
Nonlinear input design as optimal control of a Hamiltonian system
Jack Umenberger, Thomas B. Schön
We propose an input design method for a general class of parametric probabilistic models, including nonlinear dynamical systems with process noise. The goal of the procedure is to…
Specialized Interior Point Algorithm for Stable Nonlinear System Identification
Jack Umenberger, Ian R. Manchester
Estimation of nonlinear dynamic models from data poses many challenges, including model instability and non-convexity of long-term simulation fidelity. Recently Lagrangian relaxati…
Real-Time Planning with Primitives for Dynamic Walking over Uneven Terrain
Ian R. Manchester, Jack Umenberger
We present an algorithm for receding-horizon motion planning using a finite family of motion primitives for underactuated dynamic walking over uneven terrain. The motion primitives…