4 papers
Adaptive Control of Unknown Linear Switched Systems via Policy Gradient Methods
Felix Laurent, Feiran Zhao, Jaap Eising +1
We consider the policy gradient adaptive control (PGAC) framework, which adaptively updates a control policy in real time, by performing data-based gradient descent steps on the li…
Policy Gradient Adaptive Control for the LQR: Indirect and Direct Approaches
Feiran Zhao, Alessandro Chiuso, Florian Dörfler
Motivated by recent advances of reinforcement learning and direct data-driven control, we propose policy gradient adaptive control (PGAC) for the linear quadratic regulator (LQR),…
Regularization for Covariance Parameterization of Direct Data-Driven LQR Control
Feiran Zhao, Alessandro Chiuso, Florian Dörfler
As the benchmark of data-driven control methods, the linear quadratic regulator (LQR) problem has gained significant attention. A growing trend is direct LQR design, which finds th…
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)…