activity
20202025
most citedRecurrent Model Predictive Control: Learning an Explicit Recurrent Controller for Nonlinear Systems

14 citations · 37 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2025

Predictive Lagrangian Optimization for Constrained Reinforcement Learning

Tianqi Zhang, Puzhen Yuan, Guojian Zhan +6

Constrained optimization is popularly seen in reinforcement learning for addressing complex control tasks. From the perspective of dynamic system, iteratively solving a constrained…

cs.RO2021★ 12 cited

Fixed-Dimensional and Permutation Invariant State Representation of Autonomous Driving

Jingliang Duan, Dongjie Yu, Shengbo Eben Li +4

In this paper, we propose a new state representation method, called encoding sum and concatenation (ESC), for the state representation of decision-making in autonomous driving. Unl…

cs.RO2021★ 8 cited

Model-based Constrained Reinforcement Learning using Generalized Control Barrier Function

Haitong Ma, Jianyu Chen, Shengbo Eben Li +4

Model information can be used to predict future trajectories, so it has huge potential to avoid dangerous region when implementing reinforcement learning (RL) on real-world tasks,…

eess.SY2021★ 2 cited

Feasibility Enhancement of Constrained Receding Horizon Control Using Generalized Control Barrier Function

Haitong Ma, Xiangteng Zhang, Shengbo Eben Li +3

Receding horizon control (RHC) is a popular procedure to deal with optimal control problems. Due to the existence of state constraints, optimization-based RHC often suffers the not…

eess.SY2021

Recurrent Model Predictive Control

Zhengyu Liu, Jingliang Duan, Wenxuan Wang +5

This paper proposes an off-line algorithm, called Recurrent Model Predictive Control (RMPC), to solve general nonlinear finite-horizon optimal control problems. Unlike traditional…

eess.SY2021★ 14 cited

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…

eess.SY2020★ 1 cited

Continuous-time finite-horizon ADP for automated vehicle controller design with high efficiency

Ziyu Lin, Jingliang Duan, Shengbo Eben Li +2

The design of an automated vehicle controller can be generally formulated into an optimal control problem. This paper proposes a continuous-time finite-horizon approximate dynamicp…