Finite-horizon neural network-based optimal control design for affine nonlinear continuous-time systems

Qiming Zhao; Hao Xu; Travis Dierks; S. Jagannathan

doi:10.1109/IJCNN.2013.6707062

Finite-horizon neural network-based optimal control design for affine nonlinear continuous-time systems

Qiming Zhao
, Hao Xu
, Travis Dierks
, S. Jagannathan

Electrical and Computer Engineering

Missouri University of Science and Technology
DRS Sustainment Systems Inc.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	2013 International Joint Conference on Neural Networks, IJCNN 2013
DOIs	https://doi.org/10.1109/IJCNN.2013.6707062
State	Published - 2013
Event	2013 International Joint Conference on Neural Networks, IJCNN 2013 - Dallas, TX, United States Duration: Aug 4 2013 → Aug 9 2013

Publication series

Name	Proceedings of the International Joint Conference on Neural Networks

Conference

Conference	2013 International Joint Conference on Neural Networks, IJCNN 2013
Country/Territory	United States
City	Dallas, TX
Period	8/4/13 → 8/9/13

ASJC Scopus Subject Areas

Software
Artificial Intelligence

Keywords

finite-horizon
Hamilton-Jacobi-Bellman equation
neural network
optimal control

Access to Document

10.1109/IJCNN.2013.6707062

Cite this

Finite-horizon neural network-based optimal control design for affine nonlinear continuous-time systems. / Zhao, Qiming; Xu, Hao; Dierks, Travis et al.
2013 International Joint Conference on Neural Networks, IJCNN 2013. 2013. 6707062 (Proceedings of the International Joint Conference on Neural Networks).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhao, Q, Xu, H, Dierks, T & Jagannathan, S 2013, Finite-horizon neural network-based optimal control design for affine nonlinear continuous-time systems. in 2013 International Joint Conference on Neural Networks, IJCNN 2013., 6707062, Proceedings of the International Joint Conference on Neural Networks, 2013 International Joint Conference on Neural Networks, IJCNN 2013, Dallas, TX, United States, 8/4/13. https://doi.org/10.1109/IJCNN.2013.6707062

@inproceedings{7756598143a547a5a34b205144b630fd,

title = "Finite-horizon neural network-based optimal control design for affine nonlinear continuous-time systems",

keywords = "finite-horizon, Hamilton-Jacobi-Bellman equation, neural network, optimal control",

author = "Qiming Zhao and Hao Xu and Travis Dierks and S. Jagannathan",

year = "2013",

doi = "10.1109/IJCNN.2013.6707062",

language = "English",

isbn = "9781467361293",

series = "Proceedings of the International Joint Conference on Neural Networks",

booktitle = "2013 International Joint Conference on Neural Networks, IJCNN 2013",

note = "2013 International Joint Conference on Neural Networks, IJCNN 2013 ; Conference date: 04-08-2013 Through 09-08-2013",

}

TY - GEN

T1 - Finite-horizon neural network-based optimal control design for affine nonlinear continuous-time systems

AU - Zhao, Qiming

AU - Xu, Hao

AU - Dierks, Travis

AU - Jagannathan, S.

PY - 2013

Y1 - 2013

KW - finite-horizon

KW - Hamilton-Jacobi-Bellman equation

KW - neural network

KW - optimal control

UR - https://www.scopus.com/pages/publications/84893610828

UR - https://www.scopus.com/pages/publications/84893610828#tab=citedBy

U2 - 10.1109/IJCNN.2013.6707062

DO - 10.1109/IJCNN.2013.6707062

M3 - Conference contribution

AN - SCOPUS:84893610828

SN - 9781467361293

T3 - Proceedings of the International Joint Conference on Neural Networks

BT - 2013 International Joint Conference on Neural Networks, IJCNN 2013

T2 - 2013 International Joint Conference on Neural Networks, IJCNN 2013

Y2 - 4 August 2013 through 9 August 2013

ER -

Finite-horizon neural network-based optimal control design for affine nonlinear continuous-time systems

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

Other files and links

Fingerprint

Cite this