Online adaptive optimal control for continuous‐time Markov jump linear systems using a novel policy iteration algorithm-Reference-Cited by-同舟云学术

Online adaptive optimal control for continuous‐time Markov jump linear systems using a novel policy iteration algorithm

Published:2015-06 Issue:10 Volume:9 Page:1536-1543
ISSN:1751-8652
Container-title:IET Control Theory & Applications
language:en
Short-container-title:IET Control Theory & Applications

Author:

He Shuping¹,Song Jun¹,Ding Zhengtao²,Liu Fei³

Affiliation:

1. School of Electrical Engineering and Automation, Anhui UniversityHefei230601People's Republic of China

2. Control Systems Center, School of Electrical and Electronic Engineering, University of ManchesterSackville Street BuildingManchesterM13 9PLUK

3. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Institute of Automation, Jiangnan UniversityWuxi214122People's Republic of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Control and Optimization,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-cta.2014.0944

Reference43 articles.

1. Adaptive Dynamic Programming: An Introduction

2. Reinforcement learning and adaptive dynamic programming for feedback control

3. Reinforcement Learning Neural-Network-Based Controller for Nonlinear Discrete-Time Systems With Input Constraints

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