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A Fuzzy Neural Network and Application to Air-Fuel Ratio Control under Gasoline Engine Transient Condition

机译:模糊神经网络及其在汽油机瞬态空燃比控制中的应用

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In the paper, a Hendricks Mean Value Engine Model is established by using SIMULINK. At the same time, a fuzzy neural network is designed. The AFR is simulated under transient conditions. The simulation result shows that: With no controller, when throttle degree is changed intensively, the AFR errors are large, With the FNN controller, the AFR errors can be controlled to a narrow range, and the system has shorter adjust-time, smaller overshoot. So, the fuzzy neural network controller has good control performance under gasoline engine transient condition.
机译:在本文中,使用SIMULINK建立了Hendricks均值引擎模型。同时,设计了模糊神经网络。 AFR是在瞬态条件下模拟的。仿真结果表明:在无控制器的情况下,节流度变化较大时,AFR误差较大;在FNN控制器的情况下,AFR误差可控制在较窄的范围内,系统的调整时间短,过冲量小。 。因此,模糊神经网络控制器在汽油机瞬态工况下具有良好的控制性能。

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