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Model-free design of stochastic LQR controller from a primal–dual optimization perspective

  • Published:2022-06 Issue: Volume:140 Page:110253
  • ISSN:0005-1098
  • Container-title:Automatica
  • language:en
  • Short-container-title:Automatica

Author:

Li Man,Qin Jiahu,Zheng Wei Xing,Wang Yaonan,Kang Yu

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Reference27 articles.

1. On the theory of policy gradient methods: Optimality, approximation, and distribution shift;Agarwal;Journal of Machine Learning Research,2021

2. Reinforcement learning and optimal control;Bertsekas,2019

3. Convex optimization;Boyd,2004

4. Fast global convergence of natural policy gradient methods with entropy regularization;Cen;Operations Research,2021

5. On the sample complexity of the linear quadratic regulator;Dean;Foundations of Computational Mathematics,2020

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1. Lossless convexification and duality;Journal of the Franklin Institute;2024-09

2. Primal-Dual Reinforcement Learning for Zero-Sum Games in the Optimal Tracking Control;IEEE Transactions on Circuits and Systems II: Express Briefs;2024-06

3. Two-Time Scale Tracking Control of Flexible Robots With Primal-Dual Inverse Reinforcement Learning;IEEE Transactions on Neural Networks and Learning Systems;2024

4. Optimal PD Control Using Conditional GAN and Bayesian Inference;IEEE Access;2024

5. Learning Optimal Control Policy for Unknown Discrete-Time Systems;IEEE Transactions on Circuits and Systems II: Express Briefs;2023-11
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