Abstract
In this paper, a new non-model-based control design is proposed to solve the H∞ control problem for linear continuous-time systems. Our first contribution is to develop a robust control design by combining the zero-sum differential game theory with the gain assignment technique together. Compared with traditional game theory-based approaches, the obtained result allows us to assign arbitrarily the input-to-output L2 gain for a class of continuous-time linear cascaded systems. Moreover, the presence of dynamic uncertainty is tackled using the small-gain theory. Our second contribution is to give a new non-model-based robust adaptive dynamic programming (RADP) algorithm. In sharp contrast to the existing methods, the obtained algorithm is based on continuous-time value iteration (VI), and an initial stabilizing control policy is no longer required. Finally, an example of a power system is adopted to illustrate the effectiveness of the obtained algorithm.
Original language | English (US) |
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Title of host publication | 2015 54th IEEE Conference on Decision and Control, CDC 2015 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 7610-7615 |
Number of pages | 6 |
Volume | 2016-February |
ISBN (Print) | 9781479978861 |
DOIs | |
State | Published - Feb 8 2016 |
Event | 54th IEEE Conference on Decision and Control, CDC 2015 - Osaka, Japan Duration: Dec 15 2015 → Dec 18 2015 |
Other
Other | 54th IEEE Conference on Decision and Control, CDC 2015 |
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Country | Japan |
City | Osaka |
Period | 12/15/15 → 12/18/15 |
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Keywords
- Gain
- Game theory
- Games
- Optimal control
- Power system dynamics
- Robustness
- Symmetric matrices
ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization
Cite this
Data-driven robust optimal control design for uncertain cascaded systems using value iteration. / Bian, Tao; Jiang, Zhong-Ping.
2015 54th IEEE Conference on Decision and Control, CDC 2015. Vol. 2016-February Institute of Electrical and Electronics Engineers Inc., 2016. p. 7610-7615 7403422.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Data-driven robust optimal control design for uncertain cascaded systems using value iteration
AU - Bian, Tao
AU - Jiang, Zhong-Ping
PY - 2016/2/8
Y1 - 2016/2/8
N2 - In this paper, a new non-model-based control design is proposed to solve the H∞ control problem for linear continuous-time systems. Our first contribution is to develop a robust control design by combining the zero-sum differential game theory with the gain assignment technique together. Compared with traditional game theory-based approaches, the obtained result allows us to assign arbitrarily the input-to-output L2 gain for a class of continuous-time linear cascaded systems. Moreover, the presence of dynamic uncertainty is tackled using the small-gain theory. Our second contribution is to give a new non-model-based robust adaptive dynamic programming (RADP) algorithm. In sharp contrast to the existing methods, the obtained algorithm is based on continuous-time value iteration (VI), and an initial stabilizing control policy is no longer required. Finally, an example of a power system is adopted to illustrate the effectiveness of the obtained algorithm.
AB - In this paper, a new non-model-based control design is proposed to solve the H∞ control problem for linear continuous-time systems. Our first contribution is to develop a robust control design by combining the zero-sum differential game theory with the gain assignment technique together. Compared with traditional game theory-based approaches, the obtained result allows us to assign arbitrarily the input-to-output L2 gain for a class of continuous-time linear cascaded systems. Moreover, the presence of dynamic uncertainty is tackled using the small-gain theory. Our second contribution is to give a new non-model-based robust adaptive dynamic programming (RADP) algorithm. In sharp contrast to the existing methods, the obtained algorithm is based on continuous-time value iteration (VI), and an initial stabilizing control policy is no longer required. Finally, an example of a power system is adopted to illustrate the effectiveness of the obtained algorithm.
KW - Gain
KW - Game theory
KW - Games
KW - Optimal control
KW - Power system dynamics
KW - Robustness
KW - Symmetric matrices
UR - http://www.scopus.com/inward/record.url?scp=84962019061&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84962019061&partnerID=8YFLogxK
U2 - 10.1109/CDC.2015.7403422
DO - 10.1109/CDC.2015.7403422
M3 - Conference contribution
AN - SCOPUS:84962019061
SN - 9781479978861
VL - 2016-February
SP - 7610
EP - 7615
BT - 2015 54th IEEE Conference on Decision and Control, CDC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
ER -