Repetitive Learning Control of a Flexible Whisker in Tip Contact with an Unknown Surface

Abstract

Repetitive contact imaging uses a flexible whisker attached to a two-axis robot through a load cell. Assuming small deformations and rotations, the pitch axis decouples from the yaw. The yaw axis, under proportional—integral—derivative control, sweeps periodically back and forth across the object while the pitch axis, under repetitive learning (RL) control, maintains a uniform contact force. Once the RL controller converges, the three-dimensional contact points can be determined using an elastica algorithm. The RL controller is proven stable based on a distributed parameter beam model and is experimentally shown to provide a stable performance with improved moment regulation when compared with under proportional-derivative control.

Keywords

Repetitive learning control distributed parameter systems object identification robotics

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