KCRL: Krasovskii-Constrained Reinforcement Learning with Guaranteed Stability in Nonlinear Discrete-Time Systems-Reference-Cited by-同舟云学术

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KCRL: Krasovskii-Constrained Reinforcement Learning with Guaranteed Stability in Nonlinear Discrete-Time Systems

Published:2023-12-13 Issue: Volume: Page:
ISSN:
Container-title:2023 62nd IEEE Conference on Decision and Control (CDC)
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Author:

Lale Sahin¹,Shi Yuanyuan²,Qu Guannan³,Azizzadenesheli Kamyar⁴,Wierman Adam¹,Anandkumar Anima¹

Affiliation:

1. Caltech,Department of Computing and Mathematical Sciences

2. University of California San Diego,Department of Electrical and Computer Engineering

3. Carnegie Mellon University,Department of Electrical and Computer Engineering

4. Nvidia Corporation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10383192/10383193/10384011.pdf?arnumber=10384011

Reference51 articles.

1. Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection

2. Reinforcement Learning for Decision-Making and Control in Power Systems

3. Flow: Architecture and benchmarking for reinforcement learning in traffic control;Wu;arXiv preprint,2017

4. Stable online control of linear time-varying systems;Qu

5. Continuous control with deep reinforcement learning;Lillicrap;arXiv preprint,2015

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1. Tensor product model transformation-based reinforcement learning neural network controller with guaranteed stability;Neurocomputing;2024-12

2. Neural Operator Approximations for Boundary Stabilization of Cascaded Parabolic PDEs;International Journal of Adaptive Control and Signal Processing;2024-09-02

3. Nonlinear dynamical system approximation and adaptive control based on hybrid‐feed‐forward recurrent neural network: Simulation and stability analysis;Expert Systems;2024-05-05

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