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20202024
most citedRecurrent Model Predictive Control: Learning an Explicit Recurrent Controller for Nonlinear Systems

14 citations · 30 across the 9 of their papers we have counts for

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6 papers · 1 filter

eess.SY2024

An Explicit Discrete-Time Dynamic Vehicle Model with Assured Numerical Stability

Guojian Zhan, Qiang Ge, Haoyu Gao +3

Numerical stability is of great significance for discrete-time dynamic vehicle model. Among the unstable factors, low-speed singularity stands out as one of the most challenging is…

eess.SY2021

Approximate Optimal Filter for Linear Gaussian Time-invariant Systems

Kaiming Tang, Shengbo Eben Li, Yuming Yin +4

State estimation is critical to control systems, especially when the states cannot be directly measured. This paper presents an approximate optimal filter, which enables to use pol…

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

Ternary Policy Iteration Algorithm for Nonlinear Robust Control

Jie Li, Shengbo Eben Li, Yang Guan +3

The uncertainties in plant dynamics remain a challenge for nonlinear control problems. This paper develops a ternary policy iteration (TPI) algorithm for solving nonlinear robust c…

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…