{'fraction_non_alphanumeric': 0.013001083423618635, 'fraction_numerical': 0.0, 'mean_word_length': 5.372413793103449, '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}}
Control of MIMO nonlinear systems via approximate model inversion

In this paper, we propose a numerical technique for reference tracking control of discrete-time MIMO nonlinear systems. The technique is based on the derivation of an auxiliary predictor model and on the online computation of an approximate model inversion control sequence. If the predictor model is assumed to be polynomial, then the control input is computed at each time interval by solving a polynomial optimization problem by means of a cyclic coordinate minimization technique. This technique is numerically efficient and guarantees convergence to a so-called coordinate-wise minimum point. We provide a formal proof for boundedness of the tracking error and closed-loop stability of approximate model inversion control. A numerical example involving therapy control for a diabetic patient illustrates the practical potential of the proposed method.