Adjoints of Hamiltonian systems and iterative learning control
Adjoints of Hamiltonian systems and iterative learning control
复制标题
哈密顿系统的伴随物和迭代学习控制
DOI：
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
T. Sugie
中科院分区：
文献类型：
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作者：
K. Fujimoto;T. Sugie
研究了Hamilton控制系统的变分系统及其伴随系统，并将其应用于一类机电系统的迭代学习控制。首先，阐明了这类系统变分的自伴结构。在此基础上提出了一种新的迭代学习控制方案，该方法既不需要知道目标系统的物理参数，也不需要知道输出信号的时间导数。文中还导出了一种具体有效的机械系统学习算法。
This paper is concerned with a study on the variational systems and their adjoints of Hamiltonian control systems and its application to iterative learning control, which is applicable to a class of electro-mechanical systems. First of all, the self-adjoint structure of the variational of those systems is clarified. Then a novel iterative learning control scheme is proposed based on it. This method does not require either the knowledge of physical parameters of the target system nor the time derivatives of the output signals. A concrete and effective learning algorithm for mechanical systems is also derived.