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    • Research on Diesel Engine Speed Regulation Algorithm Based on Reinforcement Learning
    DOI：10.13949/j.cnki.nrjgc.2024.04.009
    Key Words:diesel engine speed regulation  proportional integral derivative（PID） controller  reinforcement learning algorithm  nonlinear complex system
    Author NameAffiliationE-mail
    YAO Chong College of Power and Energy Engineering， Harbin Engineering University， Harbin 150001， China yaochong@hrbeu.edu.cn 
    DONG Xun College of Power and Energy Engineering， Harbin Engineering University， Harbin 150001， China dongxun@hrbeu.edu.cn 
    LI Rui* College of Power and Energy Engineering， Harbin Engineering University， Harbin 150001， China lirui_heu@hrbeu.edu.cn 
    LONG Yun College of Power and Energy Engineering， Harbin Engineering University， Harbin 150001， China 870449195@qq.com 
    SONG Enzhe College of Power and Energy Engineering， Harbin Engineering University， Harbin 150001， China sez2005@hrbeu.edu.cn 
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    Abstract:In order to better regulate the speed of diesel engines， a reinforcement learning proportional-integral-derivative（PID） controller was proposed and applied to diesel engine speed control. Based on the soft actor-critic（SAC） algorithm with continuous action space， combined with a continuous PID controller， a reinforcement learning PID controller that can replace the speed loop of traditional PID control was designed. The design of input-output and reward functions based on the actor-critic framework was optimized to match the characteristics of diesel engines. Random actions were used to increase optimization efficiency， forming a network interaction structure for SAC-PID control of diesel engine speed， achieving the effect of quickly adjusting speed and reducing stabilization time. A MATLAB/Simulink average model was constructed using the diesel engine D6114 as the prototype， and the effectiveness of the simulation model was verified using experimental data. The average value model was used to simulate the effectiveness of this control algorithm. The simulation verification results show that the SAC-PID algorithm reduces the overshoot of the diesel engine speed response curve， makes the response time faster， and has stronger robustness. The SAC-PID control load transient speed regulation rate and stability time have reached the first level accuracy index， and the joint control effect of SAC algorithm is better than other algorithms.
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