文章摘要
Liu Wenhua (刘雯华)*,Zhang Jinjie*,Zhou Chao*,Wang Yao*,Sun Xu**,Hong Huaibing**.[J].高技术通讯(英文),2020,(3):243~252
A novel flow control scheme for reciprocating compressor based on adaptive predictive PID control
  
DOI:doi:10.3772/j.issn.1006-6748.2020.03.002
中文关键词: 
英文关键词: reciprocating compressor, capacity control, predictive PID control, internal model control (IMC)
基金项目:
Author NameAffiliation
Liu Wenhua (刘雯华)* (*Compressor Health and Intelligent Monitoring Center of National Key Laboratory of Compressor Technology, Beijing University of Chemical Technology, Beijing 100029, P.R.China) 
Zhang Jinjie* (*Compressor Health and Intelligent Monitoring Center of National Key Laboratory of Compressor Technology, Beijing University of Chemical Technology, Beijing 100029, P.R.China) 
Zhou Chao* (*Compressor Health and Intelligent Monitoring Center of National Key Laboratory of Compressor Technology, Beijing University of Chemical Technology, Beijing 100029, P.R.China) 
Wang Yao* (*Compressor Health and Intelligent Monitoring Center of National Key Laboratory of Compressor Technology, Beijing University of Chemical Technology, Beijing 100029, P.R.China) 
Sun Xu** (**Beijing Key Laboratory of Health Monitoring Control and Fault Self-Recovery for High-End Machinery, Beijing University of Chemical Technology, Beijing 100029, P.R.China) 
Hong Huaibing** (**Beijing Key Laboratory of Health Monitoring Control and Fault Self-Recovery for High-End Machinery, Beijing University of Chemical Technology, Beijing 100029, P.R.China) 
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中文摘要:
      
英文摘要:
      In the process of capacity regulation of reciprocating compressor, the frequent change of inlet temperature and pressure makes the control of exhaust flow unstable, resulting in the high pressure ratio of the intermediate stage. At last the compressor cannot operate safely. To solve the problem, a novel flow control scheme based on inlet temperature and pressure ratio is proposed. In this scheme, the intake model of the cylinder under the capacity regulation condition is established to calculate the load of the first cylinder. Then, the adaptive predictive PID(APPID) controller is designed to control the pressure ratio of other stages, and the grey prediction model is used to predict the pressure output to overcome the system delay. To solve the problem of control parameters tuning, an improved particle swarm optimization (PSO) algorithm is adopted to obtain the optimal control parameters.The effectiveness of the adaptive predictive PID control method is verified by a two-stage compressor model simulation.Finally, the flow control scheme is applied to the actual four-stage air reciprocating compressor flow control system. Although the temperature difference is greater than 15℃, the compressor exhaust flow is maintained at the set value and the pressure ratio is also maintained stable. At the same time, the compressor pressure ratio can be quickly adjusted without overshoot. The application result further verifies the feasibility and effectiveness of the scheme.
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