基于模糊PID的压缩机吸气干度控制仿真研究
Simulation Study on Suction Vapor Quality Control of Compressor Based on Fuzzy PID
摘要: 为了解决R32制冷系统压缩机排气温度高的问题，采用压缩机少量吸气带液能够有效降低排气温度并提高系统循环效率，且滚动转子式压缩机具有一定的抗湿压缩能力。如何精确稳定控制吸气干度是亟待解决的问题，本文针对压缩机吸气干度控制，设计了参数自整定模糊PID控制系统，并进一步使用粒子群算法对模糊控制的量化因子和比例因子进行优化。通过对传统PID控制、参数自整定模糊PID控制以及粒子群优化后的模糊PID控制进行仿真分析，结果表明模糊PID控制相比PID控制超调量减少了3.8%，控制时间缩短了20%，而粒子群算法优化过后的模糊PID相比未优化超调量进一步减少了4.3%，控制时间缩短了11%。
Abstract: In order to solve the problem of high discharge temperature of the R32 refrigeration system com-pressor, Suction vapor-liquid mixture refrigerant can effectively reduce the discharge temperature and improve the system’s circulation efficiency. Moreover, the rolling rotor compressor has certain anti-wet compression ability. How to accurately and stably control the suction suction vapor quality is an urgent problem to be solved. In this paper, for the control of compressor suction vapor quality, a parameter self-tuning fuzzy PID control system is designed, and further, the particle swarm opti-mization algorithm is used to optimize the quantization factor and proportion factor of the fuzzy control. Through simulation analysis of PID control, parameter self-tuning fuzzy PID control, and fuzzy PID control after particle swarm optimization, the results show that compared with PID con-trol, fuzzy control reduces overshoot by 3.8% and shortens control time by 20%, and after particle swarm optimization, fuzzy PID control further reduces overshoot by 4.3% and shortens control time by 11%.
文章引用：任凯, 陶乐仁. 基于模糊PID的压缩机吸气干度控制仿真研究[J]. 建模与仿真, 2023, 12(4): 3684-3696. https://doi.org/10.12677/MOS.2023.124338

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