Based on Q-Learning Optimal Tracking Control Schemes for Linear Itô Stochastic Systems With Markovian Jumps
Author:
Affiliation:
1. School of Computer Science and Engineering, Northeastern University, Shenyang, China
2. School of Information Science and Engineering, Northeastern University, Shenyang, China
Funder
Postdoctoral Innovative Talent Support Program in 2022
National Key Research and Development Program of China
National Natural Science Foundation of China
Liaoning Revitalization Talents Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/8920/10061496/09933905.pdf?arnumber=9933905
Reference20 articles.
1. Fault-Tolerant Control for Stochastic Switched IT2 Fuzzy Uncertain Time-Delayed Nonlinear Systems
2. Fuzzy Adaptive Optimal Consensus Fault-Tolerant Control for Stochastic Nonlinear Multi-Agent Systems
3. Q-learning for continuous-time linear systems: A model-free infinite horizon optimal control approach
4. Parallel Optimal Tracking Control Schemes for Mode-Dependent Control of Coupled Markov Jump Systems via Integral RL Method
5. Learning Control Supported by Dynamic Event Communication Applying to Industrial Systems
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