Optimal Guidance Law Design with Overload Saturation via Adaptive Dynamic Programming and Policy Iteration-Reference-Cited by-同舟云学术

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Optimal Guidance Law Design with Overload Saturation via Adaptive Dynamic Programming and Policy Iteration

Published:2023-07-24 Issue: Volume: Page:
ISSN:
Container-title:2023 42nd Chinese Control Conference (CCC)
language:
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Author:

Pengfei Shi¹,Jianglong Yu¹,Yongzhao Hua²,Dong Guo³,Xiwang Dong²,Zhang Ren¹

Affiliation:

1. School of Automation Science and Electrical Engineering, Beihang University,Beijing,P. R. China,100191

2. Institute of Artificial Intelligence, Beihang University,Beijing,P. R. China,100191

3. China Academy of Launch Vehicle Technology,Beijing,P. R. China,100076

Funder

National Natural Science Foundation of China

Beijing Natural Science Foundation

Fundamental Research Funds for the Central Universities

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10239690/10239711/10239975.pdf?arnumber=10239975

Reference19 articles.

1. Q-learning solution for optimal consensus control of discrete-time multiagent systems using reinforcement learning

2. Off-Policy Reinforcement Learning for Synchronization in Multiagent Graphical Games

3. Distributed Optimal Consensus Control for Multiagent Systems With Input Delay

4. Optimal Synchronization Control of Multiagent Systems With Input Saturation via Off-Policy Reinforcement Learning

5. Distributed optimal consen-sus control for nonlinear multiagent system with unknown dynamic;zhang;IEEE Transactions on Neural Networks and Learning Systems,2017

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