中南大学学报（自然科学版）2025，Vol.56Issue(5)：1817-1825,9.DOI:10.11817/j.issn.1672-7207.2025.05.010
基于模糊PIλDμ的气液两相混合式低温氮气射流温度控制方法
A temperature control method for gas-liquid two-phase flow mixing low-temperature nitrogen jet based on fuzzy PIλDμ
摘要
Abstract
In order to achieve precise control of the cooling temperature of low-temperature nitrogen jet in cryogenic machining and solve the problems of strong nonlinearity,limited input,and slow response,a fuzzy fractional order PID control method with anti-integral saturation function was proposed.Firstly,based on the hardware structure of the gas-liquid mixing system,the simulation model of the cryogenic jet pipeline was established on the AMESim platform.The dynamic characteristics of the nitrogen transmission process were characterized by multi-physical field coupling simulation.Secondly,taking the pipeline model as the control object,a fuzzy fractional-order PID controller with dual-input and triple-output was designed.Temperature deviation and temperature difference were used as fuzzy inputs,while parameter corrections Δkp,Δki,and Δkd were used as outputs.The control parameters were dynamically corrected based on 49 Sugeno-type fuzzy rules,and the anti-integral saturation algorithm was integrated to suppress actuator saturation.Finally,the AMESim-Simulink co-simulation environment was constructed.With the settling time and steady-state error as optimization objectives,the improved particle swarm optimization algorithm was used to optimize the control parameters kp,ki,kd,and fractional orders λ,μ.The results show that at the target temperatures of-80℃and-140℃,the proposed method achieves 58.27％and 25.85％reduction in settling time compared to the optimal PID controller,respectively,and 64.82％and 11.17％reduction compared to the fractional-order PID controller.The peak time shows 29.80％and 8.53％reduction versus the optimal PID,and 34.77％and 9.81％reduction versus the fractional-order PID,respectively,and the steady-state temperature error is controlled within±0.5℃.The controller effectively improves the dynamic response and steady-state accuracy of the cryogenic jet system through the coordination of fuzzy logic adaptability and fractional order operator memory characteristics.关键词
超低温加工/温度控制/模糊PIλDμ/低温氮气射流/AMESim-Simulink联合仿真Key words
cryogenic machining/temperature control/fuzzy PIλDμ/cryogenic nitrogen jet/AMESim-simulink co-simulation分类
矿业与冶金引用本文复制引用
李虓猇,杨东..基于模糊PIλDμ的气液两相混合式低温氮气射流温度控制方法[J].中南大学学报（自然科学版）,2025,56(5):1817-1825,9.基金项目
国家自然科学基金资助项目(52005002),安徽省自然科学基金资助项目(1908085QE230),安徽省高等学校自然科学研究重大项目(2023AH040010)(Project(52005002)supported by the National Natural Science Foundation of China （52005002）
Project(1908085QE230)supported by the Natural Science Foundation of Anhui Province （1908085QE230）
Project(2023AH040010)supported by the Key Project of Natural Science Research in Universities of Anhui Province) （2023AH040010）
