机械臂的学习控制系统具有将已有知识应用于其他问题的能力

S. Hayakawa, T. Oka, T. Suzuki, S. Okuma
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引用次数: 2

摘要

传统的学习控制系统不具备泛化能力,因为一个轨迹的输入数据是通过学习获得的,不能应用到其他轨迹上。本文提出了一种新的神经网络学习控制系统。神经网络可以根据从常规学习过程中获得的数据来获取和记忆系统的动态。利用该系统,我们可以得到任意轨迹的良好近似输入数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Learning control system for manipulators with the ability to use already acquired knowledge in other problem
The conventional learning control system doesn't have the capability of generalization, because input data for one trajectory, acquired by learning, cannot be applied to other trajectories. In this paper, we propose the new learning control system with the neural network. The neural network can acquire and memorize the dynamics of the system based on the data obtained from conventional learning process. By using this system, we can obtain the well-approximated input data for any trajectory.
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