Measuring the Performance of Iterative Learning Control Systems

Iterative learning control has the potential to significantly improve the tracking performance of repeating trajectory control systems. However, until now little attempt has been made to measure this performance quantitatively. A new iterative learning control performance index PI_N is introduced which allows direct, quantitative, performance comparison of different algorithms, or alternatively a single algorithm which has variable tuning parameters. In particular, PI _N can be used as a tool for selecting and adjusting algorithm tuning parameters. Application of the new performance index is demonstrated with both simulation studies and practical implementation on a gantry robot