{'fraction_non_alphanumeric': 0.018327605956471937, 'fraction_numerical': 0.0, 'mean_word_length': 5.881889763779528, '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}}
Matrix Inequalities Based Robust Model Predictive Control for Vehicle Considering Model Uncertainties and External Disturbances*

Model uncertainties and external disturbances can inevitably affect vehicle dynamic control accuracy and even cause the vehicle system to be unstable and unsafe. Therefore, vehicle dynamic controller must be able to suppress the influence of model uncertainties and external disturbances on vehicle dynamic control performance. To this aim, we design a matrix inequalities (both bilinear matrix inequalities (BMIs) and linear matrix inequalities (LMIs) are involved) based robust model predictive controller for vehicle dynamic control. Robust positive invariant (RPI) set is used to guarantee the controller is robust and to construct the matrix inequality equations. We test the usefulness of the proposed controller via a numerical example.