Abstract
This paper proposes a novel policy-iteration-based adaptive optimal scheme for uncertain continuous-time linear systems with excitation signals. The proposed method can solve the related linear quadratic optimal control problem in online fashion exactly and safely. In order to maintain persistence excitation condition, the controller injects the small excitation signals to the system. For this linear system with excitation signals, the policy iteration (PI) technique is investigated to adaptively find the optimal control law in the presence of both internal uncertainties and known excitation signals. For the proposed PI technique, the stability of the closed-loop system and convergence to the optimal solution are mathematically proven. Numerical simulations are carried out to verify the effectiveness of the proposed method.
| Original language | English |
|---|---|
| Title of host publication | ICCAS 2010 - International Conference on Control, Automation and Systems |
| Pages | 646-651 |
| Number of pages | 6 |
| Publication status | Published - 2010 Dec 1 |
| Event | International Conference on Control, Automation and Systems, ICCAS 2010 - Gyeonggi-do, Korea, Republic of Duration: 2010 Oct 27 → 2010 Oct 30 |
Other
| Other | International Conference on Control, Automation and Systems, ICCAS 2010 |
|---|---|
| Country | Korea, Republic of |
| City | Gyeonggi-do |
| Period | 10/10/27 → 10/10/30 |
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All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Control and Systems Engineering
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Policy-iteration-based adaptive optimal control for uncertain continuous-time linear systems with excitation signals. / Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho.
ICCAS 2010 - International Conference on Control, Automation and Systems. 2010. p. 646-651 5670225.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Policy-iteration-based adaptive optimal control for uncertain continuous-time linear systems with excitation signals
AU - Lee, Jae Young
AU - Park, Jin Bae
AU - Choi, Yoon Ho
PY - 2010/12/1
Y1 - 2010/12/1
N2 - This paper proposes a novel policy-iteration-based adaptive optimal scheme for uncertain continuous-time linear systems with excitation signals. The proposed method can solve the related linear quadratic optimal control problem in online fashion exactly and safely. In order to maintain persistence excitation condition, the controller injects the small excitation signals to the system. For this linear system with excitation signals, the policy iteration (PI) technique is investigated to adaptively find the optimal control law in the presence of both internal uncertainties and known excitation signals. For the proposed PI technique, the stability of the closed-loop system and convergence to the optimal solution are mathematically proven. Numerical simulations are carried out to verify the effectiveness of the proposed method.
AB - This paper proposes a novel policy-iteration-based adaptive optimal scheme for uncertain continuous-time linear systems with excitation signals. The proposed method can solve the related linear quadratic optimal control problem in online fashion exactly and safely. In order to maintain persistence excitation condition, the controller injects the small excitation signals to the system. For this linear system with excitation signals, the policy iteration (PI) technique is investigated to adaptively find the optimal control law in the presence of both internal uncertainties and known excitation signals. For the proposed PI technique, the stability of the closed-loop system and convergence to the optimal solution are mathematically proven. Numerical simulations are carried out to verify the effectiveness of the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=78751528766&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78751528766&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:78751528766
SN - 9781424474530
SP - 646
EP - 651
BT - ICCAS 2010 - International Conference on Control, Automation and Systems
ER -