593 citations · 1.8k across the 57 of their papers we have counts for
12 papers · 1 filter
NANO: A Unified Optimization Framework for Nonlinear Gaussian Filtering
Zhenxuan Ma, Haoning Wang, Wenhan Cao +1
Conventional Gaussian filtering typically approximates nonlinear models or their statistical moments and retains the Kalman update structure. The resulting approximation errors can…
Scalable Synthesis of Formally Verified Neural Value Function for Hamilton-Jacobi Reachability Analysis
Yujie Yang, Hanjiang Hu, Tianhao Wei +2
Hamilton-Jacobi (HJ) reachability analysis provides a formal method for guaranteeing safety in constrained control problems. It synthesizes a value function to represent a long-ter…
Controllability Test for Nonlinear Datatic Systems
Yujie Yang, Letian Tao, Likun Wang +1
Controllability is a fundamental property of control systems, serving as the prerequisite for controller design. While controllability test is well established in modelic (i.e., mo…
The Feasibility Theory of Constrained Reinforcement Learning: A Tutorial Study
Yujie Yang, Zhilong Zheng, Masayoshi Tomizuka +2
Satisfying safety constraints is a priority concern when solving optimal control problems (OCPs). Due to the existence of infeasibility phenomenon, where a constraint-satisfying so…
Canonical Form of Datatic Description in Control Systems
Guojian Zhan, Ziang Zheng, Shengbo Eben Li
The design of feedback controllers is undergoing a paradigm shift from modelic (i.e., model-driven) control to datatic (i.e., data-driven) control. Canonical form of state space mo…
On the Stability of Datatic Control Systems
Yujie Yang, Zhilong Zheng, Shengbo Eben Li
The development of feedback controllers is undergoing a paradigm shift from (model-driven) control to (data-driven) control. Stability, as a f…
Robust Bayesian Inference for Moving Horizon Estimation
Wenhan Cao, Chang Liu, Zhiqian Lan +3
The accuracy of moving horizon estimation (MHE) suffers significantly in the presence of measurement outliers. Existing methods address this issue by treating measurements leading…
Recurrent Model Predictive Control: Learning an Explicit Recurrent Controller for Nonlinear Systems
Zhengyu Liu, Jingliang Duan, Wenxuan Wang +4
This paper proposes an offline control algorithm, called Recurrent Model Predictive Control (RMPC), to solve large-scale nonlinear finite-horizon optimal control problems. It can b…
Hierarchical Reinforcement Learning for Self-Driving Decision-Making without Reliance on Labeled Driving Data
Jingliang Duan, Shengbo Eben Li, Yang Guan +2
Decision making for self-driving cars is usually tackled by manually encoding rules from drivers' behaviors or imitating drivers' manipulation using supervised learning techniques.…
Adaptive dynamic programming for nonaffine nonlinear optimal control problem with state constraints
Jingliang Duan, Zhengyu Liu, Shengbo Eben Li +3
This paper presents a constrained adaptive dynamic programming (CADP) algorithm to solve general nonlinear nonaffine optimal control problems with known dynamics. Unlike previous A…
Relaxed Actor-Critic with Convergence Guarantees for Continuous-Time Optimal Control of Nonlinear Systems
Jingliang Duan, Jie Li, Qiang Ge +4
This paper presents the Relaxed Continuous-Time Actor-critic (RCTAC) algorithm, a method for finding the nearly optimal policy for nonlinear continuous-time (CT) systems with known…
Parallel Optimal Control for Cooperative Automation of Large-scale Connected Vehicles via ADMM
Zhitao Wang, Yang Zheng, Shengbo Eben Li +2
This paper proposes a parallel optimization algorithm for cooperative automation of large-scale connected vehicles. The task of cooperative automation is formulated as a centralize…