Transactions of the Institute of Systems, Control and Information Engineers
Online ISSN : 2185-811X
Print ISSN : 1342-5668
ISSN-L : 1342-5668
Iterative Learning Optimal Control of Hamiltonian Systems Based on Variational Symmetry
Kenji FUJIMOTOTetsu HORIUCHIToshiharu SUGIE
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2008 Volume 21 Issue 1 Pages 10-17

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Abstract

This paper proposes a novel iterative learning control method for Hamiltonian control systems which can solve a class of optimal control problems. First of all, a symmetric property of the input-output mappings of Hamiltonian systems is clarified which plays an important role in solving, optimal control problems by gradient method. A concrete learning algorithm is derived for mechanical systems possibly with input saturation. Furthermore, numerical simulations of a 2 link robot manipulator demonstrate the the effectiveness of the proposed method.

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