Abstract
This paper studies the adaptive and optimal output-feedback problem for continuous-time uncertain systems with nonlinear dynamic uncertainties. Data-driven output-feedback control policies are developed by approximate/adaptive dynamic programming (ADP) based on both policy iteration and value iteration methods. The obtained adaptive and optimal output-feedback controllers differ from the existing literature on the ADP in that they are derived from sampled-data systems theory and are guaranteed to be robust to dynamic uncertainties. A small-gain condition is given under which the overall system is globally asymptotically stable at the origin. An application to power systems is given to test the effectiveness of the proposed approaches.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 37-45 |
| Number of pages | 9 |
| Journal | Automatica |
| Volume | 72 |
| DOIs | |
| State | Published - Oct 1 2016 |
Fingerprint
Keywords
- Approximate/adaptive dynamic programming (ADP)
- Nonlinear dynamic uncertainty
- Output-feedback control
- Robust optimal control
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering
Cite this
Output-feedback adaptive optimal control of interconnected systems based on robust adaptive dynamic programming. / Gao, Weinan; Jiang, Yu; Jiang, Zhong-Ping; Chai, Tianyou.
In: Automatica, Vol. 72, 01.10.2016, p. 37-45.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Output-feedback adaptive optimal control of interconnected systems based on robust adaptive dynamic programming
AU - Gao, Weinan
AU - Jiang, Yu
AU - Jiang, Zhong-Ping
AU - Chai, Tianyou
PY - 2016/10/1
Y1 - 2016/10/1
N2 - This paper studies the adaptive and optimal output-feedback problem for continuous-time uncertain systems with nonlinear dynamic uncertainties. Data-driven output-feedback control policies are developed by approximate/adaptive dynamic programming (ADP) based on both policy iteration and value iteration methods. The obtained adaptive and optimal output-feedback controllers differ from the existing literature on the ADP in that they are derived from sampled-data systems theory and are guaranteed to be robust to dynamic uncertainties. A small-gain condition is given under which the overall system is globally asymptotically stable at the origin. An application to power systems is given to test the effectiveness of the proposed approaches.
AB - This paper studies the adaptive and optimal output-feedback problem for continuous-time uncertain systems with nonlinear dynamic uncertainties. Data-driven output-feedback control policies are developed by approximate/adaptive dynamic programming (ADP) based on both policy iteration and value iteration methods. The obtained adaptive and optimal output-feedback controllers differ from the existing literature on the ADP in that they are derived from sampled-data systems theory and are guaranteed to be robust to dynamic uncertainties. A small-gain condition is given under which the overall system is globally asymptotically stable at the origin. An application to power systems is given to test the effectiveness of the proposed approaches.
KW - Approximate/adaptive dynamic programming (ADP)
KW - Nonlinear dynamic uncertainty
KW - Output-feedback control
KW - Robust optimal control
UR - http://www.scopus.com/inward/record.url?scp=84978424157&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84978424157&partnerID=8YFLogxK
U2 - 10.1016/j.automatica.2016.05.008
DO - 10.1016/j.automatica.2016.05.008
M3 - Article
AN - SCOPUS:84978424157
VL - 72
SP - 37
EP - 45
JO - Automatica
JF - Automatica
SN - 0005-1098
ER -