Neural network‐based optimal tracking control for partially unknown discrete‐time non‐linear systems using reinforcement learning-Reference-Cited by-同舟云学术

Neural network‐based optimal tracking control for partially unknown discrete‐time non‐linear systems using reinforcement learning

Published:2020-12-16 Issue:2 Volume:15 Page:260-271
ISSN:1751-8644
Container-title:IET Control Theory & Applications
language:en
Short-container-title:IET Control Theory & Appl

Author:

Zhao Jingang¹^ORCID,Vishal Prateek²

Affiliation:

1. College of Information and Control Engineering Weifang University 5147 Dongfeng East Street Weifang Shandong 261061 China

2. College of Engineering The Ohio State University Columbus Ohio

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/cth2.12037

Reference55 articles.

1. Robust trajectory tracking for a scale model autonomous helicopter

2. Adaptive output feedback tracking control of a nonholonomic mobile robot

3. Adaptive actuator failure compensation for parametric strict feedback systems and an aircraft application

4. Optimal Control

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