TY - GEN
T1 - Robust adaptive dynamic programming for continuous-time linear stochastic systems
AU - Bian, Tao
AU - Jiang, Zhong Ping
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/25
Y1 - 2014/11/25
N2 - In this paper, a robust optimal control problem is investigated for continuous-time linear stochastic systems with dynamic uncertainties. A non-model based stochastic robust optimal control design methodology is employed to iteratively update the control policy online by directly using the online information. A robust adaptive dynamic programming (RADP) algorithm is developed, together with rigorous convergence and stability analysis. The effectiveness of the proposed method is also illustrated by an example of two connected inverted pendulums.
AB - In this paper, a robust optimal control problem is investigated for continuous-time linear stochastic systems with dynamic uncertainties. A non-model based stochastic robust optimal control design methodology is employed to iteratively update the control policy online by directly using the online information. A robust adaptive dynamic programming (RADP) algorithm is developed, together with rigorous convergence and stability analysis. The effectiveness of the proposed method is also illustrated by an example of two connected inverted pendulums.
UR - http://www.scopus.com/inward/record.url?scp=84919400102&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84919400102&partnerID=8YFLogxK
U2 - 10.1109/ISIC.2014.6967601
DO - 10.1109/ISIC.2014.6967601
M3 - Conference contribution
AN - SCOPUS:84919400102
T3 - 2014 IEEE International Symposium on Intelligent Control, ISIC 2014
SP - 536
EP - 541
BT - 2014 IEEE International Symposium on Intelligent Control, ISIC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Symposium on Intelligent Control, ISIC 2014
Y2 - 8 October 2014 through 10 October 2014
ER -