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为使末端执行器和软物体间的抓持力快速低超调地跟踪设定力,提出基于力外环的抓取预测控制方案。该方案通过采集软物体受到的抓持力建立灰色预测模型,可预测超前一个、两个采样周期的抓持力,将实际力、预测力形成的综合力偏差作为变参数PI力补偿器的输入,力补偿器生成位置控制系统的校正指令。力控制器可利用过去、当前和将来的抓持力信息来计算合适的控制量来对抓持力偏差进行预补偿,使末端执行器和软物体之间的动态抓取具有适应性。水果抓取试验表明,抓取预测控制可获得响应快速、超调量小和调节时间短的控制性能,减小水果抓取损伤,适合软物体抓取。
In order to track the set force quickly and low-overshadowing the grip force between the end effector and the soft object, a control scheme based on force outer loop is proposed. The program builds a gray prediction model by collecting the gripping force of soft objects, predicts the holding force one or two sampling periods ahead, and takes the comprehensive deviation formed by the actual force and the predictive force as the variable parameter PI force compensator , Force compensator generates a position control system calibration instructions. Force controllers can use past, current, and future grip information to calculate the appropriate amount of control to pre-compensate for grip bias and adapt dynamic capture between the end effector and the soft object. The results of fruit picking experiment showed that the control of picking predictive control can obtain the control performance with fast response, small overshoot and short adjusting time, which can reduce the fruit picking damage and is suitable for the crawling of soft objects.