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DEAD-BEAT CONTROL OF WALKING FOR A TORSO-ACTUATED RIMLESS WHEEL USING AN EVENT-BASED, DISCRETE, LINEAR CONTROLLER

机译:使用基于事件的离散的线性控制器的躯干致动无齿轮行走的死搏控制

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In this paper, we present dead-beat control of a torso-actuated rimless wheel model. We compute the steady state walking gait using a Poincare map. When disturbed, this walking gait takes a few steps to cancel the effect of the disturbance but our goal is to develop a faster response. To do this, we develop an event-based, linear, discrete controller designed to cancel the effect of the disturbance in a single step - a one-step dead-beat controller. The controller uses the measured deviation of the stance leg velocity at mid-stance to set the torso angle to get the wheel back to the limit cycle at the following step. We show that this linear controller can correct for a height disturbance up to 3% leg length. The same controller can be used to transition from one walking speed to another in a single step. We make the model-based controller insensitive to modeling errors by adding a small integral term allowing the robot to walk blindly on a 7° uphill incline and tolerate a 30% added mass. Finally, we report preliminary progress on a hardware prototype based on the model.
机译:在本文中,我们呈现了躯干致动无磁轮模型的死搏控制。我们使用庞的地图计算稳态步行步态。当受到干扰时,这次行走步态需要几步取消干扰的影响,但我们的目标是发展更快的回应。为此,我们开发了一个基于事件的线性,离散控制器,旨在取消扰动在单个步骤中的效果 - 一步 - 一步的死区控制器。控制器使用中间姿势处的姿态腿速度的测量偏差设定躯干角度以使车轮在以下步骤中返回极限循环。我们表明,该线性控制器可以校正高达3%腿长的高度干扰。同一控制器可用于在单个步骤中从一个步行速度转换到另一个步骤。通过添加一个小的整体术语,使基于模型的控制器对建模误差不敏感,允许机器人在7°上坡倾斜上盲目地行走并容忍30%的额外质量。最后,我们在基于模型的基础上报告了硬件原型的初步进展。

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