9 papers
Fundamental Limitations of Data-Driven Control: A Statistical Decision Perspective
Jiabao He, Feiran Zhao, Yushan Li +3
Substantial research efforts have been devoted to the design of data-driven controllers; however, comparatively less is known about their statistical performance and fundamental li…
Adaptive Linear Quadratic Control of Unknown Linear Time-Varying Systems via Policy Gradient Methods
Feiran Zhao, Florian Dörfler
Unknown linear time-varying (LTV) systems require the control policy to adapt from online closed-loop data as dynamics evolve. Existing methods usually update the policy by solving…
A Data-Enabled Primal-Dual Approach for Policy Learning with SDP Formulations
Han Wang, Feiran Zhao, Florian Dorfler
This paper develops a data-enabled primal-dual framework for learning optimal control policies for unknown linear discrete-time systems from online data. The proposed approach view…
On the Effect of Quadratic Regularization in Direct Data-Driven LQR
Manuel Klädtke, Feiran Zhao, Florian Dörfler +1
This paper proposes an explainability concept for direct data-driven linear quadratic regulation (LQR) with quadratic regularization. Our perspective follows the parametric effect…
A Bayesian Perspective on the Data-Driven LQR
Thierry Schwaller, Feiran Zhao, Florian Dörfler
The data-driven linear quadratic regulator (ddLQR) is a widely studied control method for unknown dynamical systems with disturbance. Existing approaches, both indirect, i.e., thos…
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)…