Neural network-based finite-horizon approximately optimal control of uncertain affine nonlinear continuous-time systems

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

doi:10.1109/ACC.2014.6858693

Neural network-based finite-horizon approximately optimal control of uncertain affine nonlinear continuous-time systems

Hao Xu
, Qiming Zhao
, 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	2014 American Control Conference, ACC 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1243-1248
Number of pages	6
ISBN (Print)	9781479932726
DOIs	https://doi.org/10.1109/ACC.2014.6858693
State	Published - 2014
Event	2014 American Control Conference, ACC 2014 - Portland, OR, United States Duration: Jun 4 2014 → Jun 6 2014

Publication series

Name	Proceedings of the American Control Conference
ISSN (Print)	0743-1619

Conference

Conference	2014 American Control Conference, ACC 2014
Country/Territory	United States
City	Portland, OR
Period	6/4/14 → 6/6/14

ASJC Scopus Subject Areas

Electrical and Electronic Engineering

Keywords

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

Access to Document

10.1109/ACC.2014.6858693

Cite this

Xu, H., Zhao, Q., Dierks, T., & Jagannathan, S. (2014). Neural network-based finite-horizon approximately optimal control of uncertain affine nonlinear continuous-time systems. In 2014 American Control Conference, ACC 2014 (pp. 1243-1248). Article 6858693 (Proceedings of the American Control Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2014.6858693

Neural network-based finite-horizon approximately optimal control of uncertain affine nonlinear continuous-time systems. / Xu, Hao; Zhao, Qiming; Dierks, Travis et al.
2014 American Control Conference, ACC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 1243-1248 6858693 (Proceedings of the American Control Conference).

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

Xu, H, Zhao, Q, Dierks, T & Jagannathan, S 2014, Neural network-based finite-horizon approximately optimal control of uncertain affine nonlinear continuous-time systems. in 2014 American Control Conference, ACC 2014., 6858693, Proceedings of the American Control Conference, Institute of Electrical and Electronics Engineers Inc., pp. 1243-1248, 2014 American Control Conference, ACC 2014, Portland, OR, United States, 6/4/14. https://doi.org/10.1109/ACC.2014.6858693

Xu H, Zhao Q, Dierks T, Jagannathan S. Neural network-based finite-horizon approximately optimal control of uncertain affine nonlinear continuous-time systems. In 2014 American Control Conference, ACC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 1243-1248. 6858693. (Proceedings of the American Control Conference). doi: 10.1109/ACC.2014.6858693

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Neural network-based finite-horizon approximately optimal control of uncertain affine nonlinear continuous-time systems

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

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