{'fraction_non_alphanumeric': 0.01702127659574468, 'fraction_numerical': 0.0, 'mean_word_length': 5.315436241610739, '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}}
Model-free predictive control of nonlinear systems based on linearization of partial format

A model-free predictive control algorithm based on linearization of partial format is proposed for a class of nonlinear systems which are described by NARMAX model. In the algorithm, linearization of partial format is used to convert nonlinear systems which are described by NARMAX model into linear systems which are described by a series of pseudo-partial-derivatives. Thus the nonlinear control problem is converted into a linear control problem. A novel project algorithm is used to estimate the pseudo-partial-derivatives, then we get the general model and the predictive model of the controlled system. By solving finite horizon quadratic objective function, the model-free predictive control law is obtained. Simulation result shows that the proposed algorithm is an effective strategy with excellent tracking ability and strong robustness.