控制理论(社会学)
模型预测控制
非线性系统
国家观察员
温度控制
沸腾
蒸发器
工程类
计算机科学
控制工程
机械工程
控制(管理)
热力学
热交换器
物理
量子力学
人工智能
作者
Guanru Li,Rafal Madonski,Krzysztof Lakomy,Li Sun,Kwang Y. Lee
标识
DOI:10.1016/j.applthermaleng.2022.118663
摘要
• A pumped two-phase cooling loop via minichannel boiling is fabricated. • The temperature control objective in terms of heat load variation is put forward. • The nonlinearity of flow boiling is analyzed via identification and visualization. • Extended state observer-based model predictive control is proposed. • The proposed strategy fulfills the objectives of heat load disturbance mitigation. Mechanically pumped two-phase loop (MPTL), as an emerging two-phase heat dissipation transformational technique, has made booming progress in some critical but tough cases such as space stations and high-performance chips. However, accurate temperature regulation of MPTL is intractable due to periodic heat load disturbance, measurement noise, and micro-channel boiling nonlinearity. To address these issues, an extended state observer-based model predictive control (ESOMPC) strategy is developed in this paper. To describe the process model, this paper builds an MPTL platform equipped with a micro-channel evaporator, based on which a series of sinusoidal heat load variation is carried out to show the effects on the wall temperature. Open-loop step experiments are then conducted in terms of flow rate of the working fluid so that the process model can be identified and the nonlinearity can be analyzed. Then, the ESOMPC is developed by incorporating the disturbance information in the optimization framework of the MPC. The ESO part is utilized to estimate the unknown disturbances and compensate the nonlinearity of MPTL, and thus enhance the disturbance mitigation property of the MPC algorithm. Finally, the closed-loop experiments verifies the efficacy of the proposed solution, showing smaller temperature fluctuation and shorter settling time than the conventional controller. The results indicate the great potential of the proposed ESOMPC in enhancing the temperature control accuracy of MPTL in terms of thermal management performance.
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