5 citations · 10 across the 15 of their papers we have counts for
15 papers
Verifiable Model-Free Safety Filters via Reinforcement Learning
Bihui Yin, Yiwen Lu, Yuchen Jiang +1
This paper presents a reinforcement learning approach of a model-free safety filter, drawing inspiration from the framework of model-based Predictive Safety Filters (PSFs). Similar…
Identification with Orthogonal Basis Functions: Convergence Speed, Asymptotic Bias, and Rate-Optimal Pole Selection
Jiayun Li, Yiwen Lu, Yilin Mo +1
This paper is concerned with performance analysis and pole selection problem in identifying linear time-invariant (LTI) systems using orthogonal basis functions (OBFs), a system id…
Learning to Drift with Individual Wheel Drive: Maneuvering Autonomous Vehicle at the Handling Limits
Yihan Zhou, Yiwen Lu, Bo Yang +2
Drifting, characterized by controlled vehicle motion at high sideslip angles, is crucial for safely handling emergency scenarios at the friction limits. While recent reinforcement…
Regret Analysis with Almost Sure Convergence for OBF-ARX Filter
Jiayun Li, Yiwen Lu, Yilin Mo
This paper considers the output prediction problem for an unknown Linear Time-Invariant (LTI) system. In particular, we focus our attention on the OBF-ARX filter, whose transfer fu…
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)…
Generalized Activation via Multivariate Projection
Jiayun Li, Yuxiao Cheng, Yiwen Lu +3
Activation functions are essential to introduce nonlinearity into neural networks, with the Rectified Linear Unit (ReLU) often favored for its simplicity and effectiveness. Motivat…
Consecutive Inertia Drift of Autonomous RC Car via Primitive-based Planning and Data-driven Control
Yiwen Lu, Bo Yang, Jiayun Li +3
Inertia drift is an aggressive transitional driving maneuver, which is challenging due to the high nonlinearity of the system and the stringent requirement on control and planning…
Almost Surely Regret for Adaptive LQR
Yiwen Lu, Yilin Mo
The Linear-Quadratic Regulation (LQR) problem with unknown system parameters has been widely studied, but it has remained unclear whether regret, w…
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…
A Hierarchical Control Framework for Drift Maneuvering of Autonomous Vehicles
Bo Yang, Yiwen Lu, Xu Yang +1
Drift control is significant to the safety of autonomous vehicles when there is a sudden loss of traction due to external conditions such as rain or snow. It is a challenging contr…
Two-timescale Mechanism-and-Data-Driven Control for Aggressive Driving of Autonomous Cars
Yiwen Lu, Bo Yang, Yilin Mo
The control for aggressive driving of autonomous cars is challenging due to the presence of significant tyre slip. Data-driven and mechanism-based methods for the modeling and cont…
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…