{'fraction_non_alphanumeric': 0.019756838905775075, 'fraction_numerical': 0.0, 'mean_word_length': 5.936842105263158, '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}}
A novel modeling and controlling approach for high‐order nonlinear systems

This paper proposes a completely data–driven control law for a class of high–order nonlinear systems based on their virtual characteristic models. With sampled–data techniques and estimation methods, a novel lower–order adaptive characteristic model is constructed to reduce the system complexities. Moreover, a corresponding sliding mode control law is designed, which can guarantee tracking errors of the resulting closed‐loop system converging into a predefined bound in finite time. The practical examples are provided to illuminate the effectiveness of the proposed approaches.