On learning transient, auto-tunings of learnable bandwidth and lead step in iterative learning control

Abstract

The learning transient and tracking accuracy of phase lead compensation iterative learning control are determined by its three parameters: learning gain, system learnable bandwidth and lead step. Because of the model inaccuracy, the learnable bandwidth is often chosen as a conservative value, which often degrades the learning performance. In this article, the learning transient is analysed and the tuning of learnable bandwidth and lead step are developed to achieve good learning transient and tracking accuracy simultaneously. The attractive properties include that the less dependence on system model and that the tracking error during this process keeps at a very low level. Experimental results on an industrial robot are presented to verify the tuning process.

Keywords:

• iterative learning control
• convergence
• learning transient
• learnable bandwidth tuning
• lead step tuning