Robust Control in the Worst Case Using Continuous Time Reinforcement Learning

2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC) ◽

10.1109/smc42975.2020.9283087 ◽

2020 ◽

Author(s):

Adolfo Perrusquia ◽

Wen Yu ◽

Xiaoou Li

Keyword(s):

Reinforcement Learning ◽

Robust Control ◽

Continuous Time ◽

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Continuous-time reinforcement learning for robust control under worst-case uncertainty

International Journal of Systems Science ◽

10.1080/00207721.2020.1839142 ◽

2020 ◽

pp. 1-15

Author(s):

Adolfo Perrusquía ◽

Wen Yu

Keyword(s):

Reinforcement Learning ◽

Robust Control ◽

Continuous Time ◽

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Robust control under worst‐case uncertainty for unknown nonlinear systems using modified reinforcement learning

International Journal of Robust and Nonlinear Control ◽

10.1002/rnc.4911 ◽

2020 ◽

Vol 30 (7) ◽

pp. 2920-2936 ◽

Author(s):

Adolfo Perrusquía ◽

Wen Yu

Keyword(s):

Reinforcement Learning ◽

Robust Control ◽

Nonlinear Systems ◽

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Robust control of singular systems with time delay. Part I: Continuous time case

2013 European Control Conference (ECC) ◽

10.23919/ecc.2013.6669136 ◽

2013 ◽

Author(s):

Natasa A. Kablar ◽

Vladimir Kvrgic ◽

Dragutin Lj. Debeljkovic

Keyword(s):

Robust Control ◽

Continuous Time ◽

Singular Systems

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Reinforcement Learning and Adaptive Optimal Control for Continuous-Time Nonlinear Systems: A Value Iteration Approach

IEEE Transactions on Neural Networks and Learning Systems ◽

10.1109/tnnls.2020.3045087 ◽

2021 ◽

pp. 1-10

Author(s):

Tao Bian ◽

Zhong-Ping Jiang

Keyword(s):

Optimal Control ◽

Reinforcement Learning ◽

Nonlinear Systems ◽

Continuous Time ◽

Value Iteration ◽

Adaptive Optimal Control ◽

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Policy iterations for reinforcement learning problems in continuous time and space — Fundamental theory and methods

10.1016/j.automatica.2020.109421 ◽

2021 ◽

Vol 126 ◽

pp. 109421

Author(s):

Jaeyoung Lee ◽

Richard S. Sutton

Keyword(s):

Reinforcement Learning ◽

Continuous Time ◽

Learning Problems ◽

Fundamental Theory ◽

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Interactive and Worst-Case Optimized Robust Control for Potential Application to Guaranteeing Roll Stability for Intelligent Heavy Vehicle

International Journal of Automotive Technology ◽

10.1007/s12239-021-0113-4 ◽

2021 ◽

Vol 22 (5) ◽

pp. 1291-1303

Author(s):

Yulong Liu ◽

Xuewu Ji ◽

Kaiming Yang ◽

Xiangkun He ◽

Shirou Nakano

Keyword(s):

Robust Control ◽

Potential Application ◽

Heavy Vehicle ◽

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Continuous-time on-policy neural Reinforcement Learning of working memory tasks

2015 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2015.7280636 ◽

2015 ◽

Author(s):

Davide Zambrano ◽

Pieter R. Roelfsema ◽

Sander M. Bohte

Keyword(s):

Working Memory ◽

Reinforcement Learning ◽

Continuous Time

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Adaptive Robust Control in Continuous Time

SIAM Journal on Control and Optimization ◽

10.1137/20m1336680 ◽

2021 ◽

Vol 59 (5) ◽

pp. 3912-3945

Author(s):

Theerawat Bhudisaksang ◽

Álvaro Cartea

Keyword(s):

Robust Control ◽

Continuous Time ◽

Adaptive Robust Control

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Solution to the inverse problem of minimax control and worst case disturbance for linear continuous-time systems

IEEE Transactions on Automatic Control ◽

10.1109/9.668832 ◽

1998 ◽

Vol 43 (5) ◽

pp. 670-674 ◽

Author(s):

M.M. Kogan

Keyword(s):

Inverse Problem ◽

Continuous Time ◽

Minimax Control ◽

Continuous Time Systems ◽

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Off-Policy Integral Reinforcement Learning Method to Solve Nonlinear Continuous-Time Multiplayer Nonzero-Sum Games

IEEE Transactions on Neural Networks and Learning Systems ◽

10.1109/tnnls.2016.2582849 ◽

2017 ◽

Vol 28 (3) ◽

pp. 704-713 ◽

Author(s):

Ruizhuo Song ◽

Frank L. Lewis ◽

Qinglai Wei

Keyword(s):

Reinforcement Learning ◽

Continuous Time ◽

Learning Method

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