Reinforcement Learning Controller Design for Discrete-Time-Constrained Nonlinear Systems With Weight Initialization Method
Author:
Affiliation:
1. Department of Automation, Key Laboratory of System Control and Information Processing, Shanghai Jiao Tong University, Shanghai, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6221021/10474538/10398273.pdf?arnumber=10398273
Reference36 articles.
1. Identification and optimal control of nonlinear systems using recurrent neural networks and reinforcement learning: An overview
2. Optimal Control Design for Perturbed Constrained Networked Control Systems
3. Optimal Finite-Horizon Control for Networked Control Systems in the Presence of Random Delays and Packet Losses
4. Policy Optimization Adaptive Dynamic Programming for Optimal Control of Input-Affine Discrete-Time Nonlinear Systems
5. Self-Triggered Adaptive Dynamic Programming for Model-Free Nonlinear Systems via Generalized Fuzzy Hyperbolic Model
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1. Fuzzy-Based Optimal Control for Stochastic Nonlinear Systems With Constrained Inputs via Dynamic Event-Triggering;IEEE Transactions on Fuzzy Systems;2024-08
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