{'fraction_non_alphanumeric': 0.016036655211912942, 'fraction_numerical': 0.004581901489117984, 'mean_word_length': 5.154929577464789, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Iterative learning control — 2D control systems from theory to application

It has long been recognized that iterative learning control is a 2D system, i.e. information propagation occurs in two independent directions. In this paper, the application of so-called norm optimal iterative learning control, which has its origins in the theory of the class of 2D systems known as linear repetitive processes to an experimental testbed in the form of a chain conveyor system is reported. This includes the motivation for applying iterative learning control to such systems, the design and construction of the testbed, and its use to demonstrate that norm optimal iterative learning control gives superior performance over alternatives. As such, it provides an application for 2D systems theory where distinct advantages arise from using such a setting for modelling and control.