5 citations · 10 across the 15 of their papers we have counts for
6 papers · 1 filter
Learning-Based Efficient Approximation of Data-Enabled Predictive Control
Yihan Zhou, Yiwen Lu, Zishuo Li +2
Data-Enabled Predictive Control (DeePC) bypasses the need for system identification by directly leveraging raw data to formulate optimal control policies. However, the size of the…
MPC-Inspired Reinforcement Learning for Verifiable Model-Free Control
Yiwen Lu, Zishuo Li, Yihan Zhou +2
In this paper, we introduce a new class of parameterized controllers, drawing inspiration from Model Predictive Control (MPC). The controller resembles a Quadratic Programming (QP)…
Safe and Efficient Switching Controller Design for Partially Observed Linear-Gaussian Systems
Yiwen Lu, Yilin Mo
Switching control strategies that unite a potentially high-performance but uncertified controller and a stabilizing albeit conservative controller are shown to be able to balance s…
Safe and Efficient Switching Mechanism Design for Uncertified Linear Controller
Yiwen Lu, Yilin Mo
Sustained research efforts have been devoted to learning optimal controllers for linear stochastic dynamical systems with unknown parameters, but due to the corruption of noise, le…
Ensuring the Safety of Uncertified Linear State-Feedback Controllers via Switching
Yiwen Lu, Yilin Mo
Sustained research efforts have been devoted to learning optimal controllers for linear stochastic dynamical systems with unknown parameters, but due to the corruption of noise, le…
Safe Linear-Quadratic Dual Control with Almost Sure Performance Guarantee
Yiwen Lu, Yilin Mo
This paper considers the linear-quadratic dual control problem where the system parameters need to be identified and the control objective needs to be optimized in the meantime. Co…