most citedTernary Policy Iteration Algorithm for Nonlinear Robust Control

1 citations · 2 across the 5 of their papers we have counts for

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5 papers

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…

cs.LG2020

Model-Based Actor-Critic with Chance Constraint for Stochastic System

Baiyu Peng, Yao Mu, Yang Guan +3

Safety is essential for reinforcement learning (RL) applied in real-world situations. Chance constraints are suitable to represent the safety requirements in stochastic systems. Pr…

eess.SY20201 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.SY20201 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…