Deep Neural Network-Based Approximate Optimal Tracking for Unknown Nonlinear Systems-Reference-Cited by-同舟云学术

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Deep Neural Network-Based Approximate Optimal Tracking for Unknown Nonlinear Systems

Published:2023-05 Issue:5 Volume:68 Page:3171-3177
ISSN:0018-9286
Container-title:IEEE Transactions on Automatic Control
language:
Short-container-title:IEEE Trans. Automat. Contr.

Author:

Greene Max L.¹^ORCID,Bell Zachary I.²^ORCID,Nivison Scott³^ORCID,Dixon Warren E.⁴^ORCID

Affiliation:

1. Aurora Flight Sciences, Cambridge, MA, USA

2. Munitions Directorate, Air Force Research Laboratory, Eglin AFB, Navarre, FL, USA

3. Johns Hopkins University Applied Physics Laboratory, Fort Walton Beach, FL, USA

4. Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, USA

Funder

Air Force Office of Scientific Research

Air Force Research Laboratory

ONR

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9/10109211/10049093.pdf?arnumber=10049093

Reference26 articles.

1. Concurrent learning adaptive control of linear systems with exponentially convergent bounds

2. Theory and Flight-Test Validation of a Concurrent-Learning Adaptive Controller

3. Deep Model Reference Adaptive Control

4. Deep learning;lecun;Nature,2015

5. Model-Based Reinforcement Learning for Infinite-Horizon Approximate Optimal Tracking

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