基于灰色预测控制的果蔬抓取系统设计与试验

Design and experiment of fruit and vegetable grasping system based on grey prediction control

为使末端执行器和变形果蔬间的抓持力快速低超调地跟踪设定力,提出基于灰色预测的增量式比例积分(PI)力控制算法。该算法通过采集果蔬受到的抓持力建立灰色预测模型,当预测模型精度较高或较低时,相应地加大或减小预测力偏差在综合力偏差中的权值,使力控制器可以利用过去、当前和未来的果蔬抓持力信息来计算合适的控制校正量对抓持力偏差进行预补偿,可以使控制器获得超调量小和响应快速的特点,对末端执行器和果蔬之间的动态抓持过程具有适应性。果蔬抓持试验证明了灰色预测PI力控制算法的有效性,可减小果蔬抓持损伤。

Incremental PI（proportional integral） force control algorithm was proposed based on grey prediction for making grasp force track set value quickly with small overshoot between end-effector and deformable fruit and vegetable. Grey prediction model was built by the signal of grasp force acquired from the sensor,the weights of predictive force error were increased or decreased in integrated error accordingly to the precision of predictive model. Force controller could employ the past,present and future grasp force information to calculate an appropriate control correction to pre-compensate the force error,and could yield small overshot,fast response simultaneously,so make the controller adaptive to the dynamic grasp process between fruit and end-effector. Experimental results demonstrated the efficacy of grey predictive incremental PI algorithm,which the damage of grasping fruit and vegetable could be decreased.