针对柴油机电子调速器设计开发中需解决的高实时性模型建模问题，对基于RBF神经网络的柴油机建模方法进行研究，在Matlab/Simulink环境设计辨识模型和算法，以PA6柴油机为例进行了模型辨识实验验证。结果表明，本文方法具有逼近精度高、响应速度快等优点。
For electronic governor of diesel engine design and development of model-based modeling problem need to solve the high real-time capability of model, the modeling method for diesel engine based on RBF neural network were studied. Under the environment of Matlab/Simulink, the identification model and the algorithm are designed. For PA6 diesel engine as an example for the model identification test, shows that the method has the advantages of high approximation accuracy and short response speed.
2022,44(7): 118-121 收稿日期：2021-03-06
DOI：10.3404/j.issn.1672-7649.2022.07.023
分类号：U672
基金项目：国家自然科学基金资助项目（51579242）
作者简介：吴越(1988-),男,硕士研究生,研究方向为舰船动力装置自动化及仿真技术
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