6 citations · 6 across the 2 of their papers we have counts for
6 papers
Improving Input-Output Linearizing Controllers for Bipedal Robots via Reinforcement Learning
Fernando Castañeda, Mathias Wulfman, Ayush Agrawal +4
The main drawbacks of input-output linearizing controllers are the need for precise dynamics models and not being able to account for input constraints. Model uncertainty is common…
Learning Min-norm Stabilizing Control Laws for Systems with Unknown Dynamics
Tyler Westenbroek, Fernando Castaneda, Ayush Agrawal +2
This paper introduces a framework for learning a minimum-norm stabilizing controller for a system with unknown dynamics using model-free policy optimization methods. The approach b…
Feedback Linearization for Unknown Systems via Reinforcement Learning
Tyler Westenbroek, David Fridovich-Keil, Eric Mazumdar +4
We present a novel approach to control design for nonlinear systems which leverages model-free policy optimization techniques to learn a linearizing controller for a physical plant…
Competitive Statistical Estimation with Strategic Data Sources
Tyler Westenbroek, Roy Dong, Lillian J. Ratliff +1
In recent years, data has played an increasingly important role in the economy as a good in its own right. In many settings, data aggregators cannot directly verify the quality of…
A New Solution Concept and Family of Relaxations for Hybrid Dynamical Systems
Tyler Westenbroek, Humberto Gonzalez, S. Shankar Sastry
We introduce a holistic framework for the analysis, approximation and control of the trajectories of hybrid dynamical systems which display event-triggered discrete jumps in the co…
On the Relaxation of Hybrid Dynamical Systems
Tyler Westenbroek, S. Shankar Sastry, Humberto Gonzalez
Hybrid dynamical systems have proven to be a powerful modeling abstraction, yet fundamental questions regarding the dynamical properties of these systems remain. In this paper, we…