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Modeling human skills to control dynamic systems

机译:模拟人类技能以控制动态系统

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There are many successful industrial applications of control methods based on imparting human skills. However, all applications to date are task-lever controllers, i.e., when switching from one task to another, they need to be retrained. We do not focus simply on task-level human learning control, but on how to produce a general control law in which we can input control targets, i.e., to enable us to change control targets for which controllers have not been trained. Using a dynamically stabilized but statically unstable single-wheel mobile robot - Gyrover - we use this new method to control and thus confirm the validity and efficiency of the method.
机译:基于传授人的技能,控制方法在工业上有许多成功的应用。但是,迄今为止,所有应用程序都是任务杠杆控制器,即,从一个任务切换到另一个任务时,需要对其进行重新培训。我们不仅仅着眼于任务级的人类学习控制,而是着重于如何产生一种通用的控制法则,在该法则中我们可以输入控制目标,即使我们能够更改未经训练的控制器的控制目标。使用动态稳定但静态不稳定的单轮移动机器人Gyrover,我们使用这种新方法进行控制,从而确认了该方法的有效性和效率。

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