{'fraction_non_alphanumeric': 0.024469820554649267, 'fraction_numerical': 0.0024469820554649264, 'mean_word_length': 5.324742268041237, '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}}
Application of a PID-GPC Algorithm in a Ball-Mill System

A direct-fired pulverizing system with double inlets and outlets, as an important power generating plant in thermal power stations, is characterized by non-linear, multivariable, strong coupling and a large delay. Meanwhile, a ball-mill is a typical three-input, three-output system: how to model this system and accomplish its automatic control has become a hot spot in today’s research on thermal power generation. This paper takes into account PID control, the most widely used basic control law in industrial process control, and based on the generalized predictive control algorithm, applies the proportional integral differential structured generalized predictive control algorithm (PID-GPC) to the ball-mill. This algorithm incorporates the advantages of the robustness and predictive control model of the traditional PID control algorithm. The simulation of a 300 MW power unit ball-mill pulverizing system running under a negative pressure in a given power plant in Longshan, Hebei Province shows that such an algorithm offers better robustness than general feedforward decoupling PID control and GPC control: it is also more suited to industrial application.