4 citations · 5 across the 5 of their papers we have counts for
5 papers
An Adaptive Data-Enabled Policy Optimization Approach for Autonomous Bicycle Control
Niklas Persson, Feiran Zhao, Mojtaba Kaheni +2
This paper presents a unified control framework that integrates a Feedback Linearization (FL) controller in the inner loop with an adaptive Data-Enabled Policy Optimization (DeePO)…
Asynchronous Parallel Policy Gradient Methods for the Linear Quadratic Regulator
Xingyu Sha, Feiran Zhao, Keyou You
Learning policies in an asynchronous parallel way is essential to the numerous successes of RL for solving large-scale problems. However, their convergence performance is still not…
Policy Gradient Methods for the Cost-Constrained LQR: Strong Duality and Global Convergence
Feiran Zhao, Keyou You
In safety-critical applications, reinforcement learning (RL) needs to consider safety constraints. However, theoretical understandings of constrained RL for continuous control are…
Harnessing Data for Accelerating Model Predictive Control by Constraint Removal
Zhinan Hou, Feiran Zhao, Keyou You
Model predictive control (MPC) solves a receding-horizon optimization problem in real-time, which can be computationally demanding when there are thousands of constraints. To accel…
Learning Stabilizing Controllers of Linear Systems via Discount Policy Gradient
Feiran Zhao, Xingyun Fu, Keyou You
Stability is one of the most fundamental requirements for systems synthesis. In this paper, we address the stabilization problem for unknown linear systems via policy gradient (PG)…