{'fraction_non_alphanumeric': 0.013119533527696793, 'fraction_numerical': 0.0014577259475218659, 'mean_word_length': 5.9393939393939394, '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}}
Robust stability constraints for predictive control

In this paper new conditions are presented which guarantee robust global asymptotic stability of non-linear controllers for open-loop stable non-linear systems with additive l1-norm bounded model uncertainty. The resulting robust stability constraints are control method independent, linear and very unconservative because they are updated at every sample time. Based on these new conditions a predictive control method is designed for stable linear models with additive model uncertainty. Robust global asymptotic stability and offset free tracking are guaranteed for asymptotically constant reference trajectories and disturbances.