Method for solving nonlinear control problems using humans' abilities in manual control

利用人类手动控制能力解决非线性控制问题的方法

• 批准号: 10450089
• 负责人: INOOKA Hikaru
• 金额: $ 5.12万
• 依托单位: Tohoku University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (B)
• 财政年份: 1998
• 资助国家: 日本
• 起止时间: 1998 至 2000
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-10450089/
• 关键词: nonlinear control; manual control; human operator; joystick; pendulum; computer-aided; コンピュータグラフィックス; シミュレーション

Human beings can perform various complicated control tasks without enough information about controlled objects. In order to apply such humans' abilities to wide class of nonlinear control problems, we propose a method for obtaining best control performance with manual control for the experiment corresponding to the real nonlinear control task. Then we investigate its effectiveness from various viewpoints. The main results of this research are summarized as follows :1. By changing the conditions such as a display style, an input-output gain or a time scale, the ranges of the parameters for good tasks and their correlations were examined. It was confirmed that the human's ability works effectively for a certain set of parameters.2. Displaying the score of the nonlinear object function to the operator after task, the operator could get to perform almost optimal control. It is an important result that the human beings can modify their control performance even for nonlinear criteria.3. In the digging control of a power shovel and the position control of a two-link arm, we confirmed that the operator could generate various control patterns which lead to good tasks depending on the object functions. These control performance, which cannot be obtained analytically, were achieved by humans' abilities.

人类可以在没有足够的被控对象信息的情况下执行各种复杂的控制任务。为了将人类的这种能力应用于广泛的非线性控制问题，我们提出了一种针对实际非线性控制任务的实验，通过人工控制获得最佳控制性能的方法。然后从多个角度对其有效性进行了考察。本研究的主要成果总结如下：1.研究内容：通过改变诸如显示样式、输入输出增益或时间尺度等条件，检查了良好任务的参数范围及其相关性。结果证实，人的能力在一定的参数下是有效的。在任务结束后，将非线性目标函数的分数显示给操作人员，使操作人员能够进行几乎最优的控制。这是一个重要的结果，即即使对于非线性准则，人类也可以修改自己的控制性能。在电动铲的挖掘控制和双连杆臂的位置控制中，我们证实了操作员可以根据目标函数产生各种控制模式，从而完成良好的任务。这些控制性能是无法通过解析获得的，而是通过人的能力来实现的。

项目成果

Muhammad Arif: "Iterative Learning Control Utilizing the Error Prediction Method"Journal of Intelligent and Robotic Systems. 25. 95-108 (1999)

Muhammad Arif：“利用误差预测方法进行迭代学习控制”智能与机器人系统杂志。

Takahiko Ono: "Design of Sampled-Data Control Systems via the Principle of Matching"Proceedings of the 14th World Congress of International Federation of Automatic Control. Vol.C. 43-48 (1999)

Takahiko Ono：“通过匹配原理设计采样数据控制系统”国际自动控制联合会第 14 届世界大会论文集。

Yuki ITO: "Swinging-Up of Two Pendulums by Manual Control with Computer Assistance"Interdisciplinary Information Sciences. 5・2. 117-124 (1999)

Yuki ITO：“通过计算机辅助手动控制两个摆的摆动”跨学科信息科学 5・2（1999）。

Muhammad Arif: "Experimental Study of Human Performance in High Precision Tracking Task Using Iterative Learning Technique"Interdisciplinary Information Sciences. Vol.5, No.1. 73-85 (1999)

Muhammad Arif：“利用迭代学习技术对人类在高精度跟踪任务中的表现进行实验研究”跨学科信息科学。

Yuki Ito: "Swinging-Up of Two Pendulums by Manual Control with Computer Assistance"Interdisciplinary Information Sciences. Vol.5, No.2. 117-124 (1999)

伊藤由纪：“通过计算机辅助手动控制两个摆的摆动”跨学科信息科学。