{'fraction_non_alphanumeric': 0.012690355329949238, 'fraction_numerical': 0.0, 'mean_word_length': 5.520661157024794, '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 model-free predictive controller with Laguerre polynomials

This paper presents a combined subspace system identification and model predictive control algorithm with Laguerre orthonormal functions. The term commonly used for such an approach is called model-free predictive control. The main contribution of this paper is to investigate the effect of non-stationary disturbance on the stability and performance of existing model-free predictive controllers and to propose a design approach that naturally incorporates integral action as a result of the non-stationary disturbance in the system. A mathematical model of a food extruder is used in the simulation studies for illustration purposes and for demonstrating the efficacy of the proposed model-free predictive control algorithm.