Deep reinforcement learning based active surge control for aeroengine compressors  

作　　者：Xinglong ZHANG Zhonglin LIN Runmin JI Tianhong ZHANG 

机构地区：[1]College of Energy and Power Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China [2]School of Mechanical Engineering and Automation,Fuzhou University,Fuzhou 350108,China

出　　处：《Chinese Journal of Aeronautics》2024年第7期418-438,共21页中国航空学报（英文版）

基　　金：co-supported by the National Natural Science Foundation of China(No.51976089);the Science Center for Gas Turbine Project,China(No.P2023-B-V-001-001);the China Scholarship Council(No.202306830092).

摘　　要：This study proposes an active surge control method based on deep reinforcement learning to ensure the stability of compressors when adhering to the pressure rise command across the wide operating range of an aeroengine.Initially,the study establishes the compressor dynamic model with uncertainties,disturbances,and Close-Coupled Valve(CCV)actuator delay.Building upon this foundation,a Partially Observable Markov Decision Process(POMDP)is defined to facilitate active surge control.To address the issue of unobservability,a nonlinear state observer is designed using a finite-time high-order sliding mode.Furthermore,an Improved Soft Actor-Critic(ISAC)algorithm is developed,incorporating prioritized experience replay and adaptive temperature parameter techniques,to strike a balance between exploration and convergence during training.In addition,reasonable observation variables,error-segmented reward functions,and random initialization of model parameters are employed to enhance the robustness and generalization capability.Finally,to assess the effectiveness of the proposed method,numerical simulations are conducted,and it is compared with the fuzzy adaptive backstepping method and Second-Order Sliding Mode Control(SOSMC)method.The simulation results demonstrate that the deep reinforcement learning based controller outperforms other methods in both tracking accuracy and robustness.Consequently,the proposed active surge controller can effectively ensure stable operation of compressors in the high-pressure-ratio and high-efficiency region.

关 键 词：Aeroengine surge Active surge control Moore-Greitzer model Deep reinforcement learning Soft actor-critic Nonlinear observer 

分 类 号：V231[航空宇航科学与技术—航空宇航推进理论与工程]