no code implementations • NeurIPS 2021 • Tongxin Li, Ruixiao Yang, Guannan Qu, Guanya Shi, Chenkai Yu, Adam Wierman, Steven H. Low
Motivated by online learning methods, we design a self-tuning policy that adaptively learns the trust parameter $\lambda$ with a competitive ratio that depends on $\varepsilon$ and the variation of system perturbations and predictions.
no code implementations • NeurIPS 2020 • Chenkai Yu, Guanya Shi, Soon-Jo Chung, Yisong Yue, Adam Wierman
We study the impact of predictions in online Linear Quadratic Regulator control with both stochastic and adversarial disturbances in the dynamics.
no code implementations • 12 Jun 2020 • Guannan Qu, Chenkai Yu, Steven Low, Adam Wierman
Model-free learning-based control methods have seen great success recently.
