DocumentCode :
800087
Title :
Iterative learning control of Hamiltonian systems: I/O based optimal control approach
Author :
Fujimoto, Kenji ; Sugie, Toshiharu
Author_Institution :
Dept. of Syst. Sci., Kyoto Univ., Japan
Volume :
48
Issue :
10
fYear :
2003
Firstpage :
1756
Lastpage :
1761
Abstract :
In this note, a novel iterative learning control scheme for a class of Hamiltonian control systems is proposed, which is applicable to electromechanical systems. The proposed method has the following distinguished features. This method does not require either the precise knowledge of the model of the target system or the time derivatives of the output signals. Despite the lack of information, the tracking error monotonously decreases in L2 sense and, further, perfect tracking is achieved when it is applied to mechanical systems. The self-adjoint related properties of Hamiltonian systems proven in this note play the key role in this learning control. Those properties are also useful for general optimal control. Furthermore, experiments of a robot manipulator demonstrate the effectiveness of the proposed method.
Keywords :
iterative methods; manipulators; optimal control; Hamiltonian control systems; electromechanical systems; iterative learning control; optimal control; robot manipulator; Control systems; Electromechanical systems; Iterative algorithms; Iterative methods; Manipulators; Mechanical systems; Optimal control; PD control; Robot sensing systems; Target tracking;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.2003.817908
Filename :
1235379
Link To Document :
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