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Dynamic modeling and simulation of marine diesel engine using Elman networks

机译:基于Elman网络的船用柴油机动态建模与仿真

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CODAD propulsion plants are complicated systems with hull, engine and propeller operating together. It is very important to control the loads transferring from one diesel engine operating mode to twin engines operating. During the development phase of the diesel load sharing controller, the system simulation can be used as a tool to support test and verification of the complex control algorithms. The simulation models should accurately reflect the dynamic performances of the system, especially diesel engines which is high nonlinear, time-variant and cannot be linearized owing to its wide operating range. This paper presents a modeling method, based on Elman network, of diesel engines represented only by measurement data. Comparing the measurements from a test bench and the simulation results shows that the model based on the neural network modeling method can represent dynamic behaviors of the diesel engine with good precision.
机译:CODAD推进装置是复杂的系统,船体,发动机和螺旋桨共同运行。控制从一种柴油机运行模式到双引擎运行模式的负载转移非常重要。在柴油机负载共享控制器的开发阶段,系统仿真可以用作支持测试和验证复杂控制算法的工具。仿真模型应准确反映系统的动态性能,尤其是柴油发动机,该发动机具有很高的非线性,随时间变化并且由于其较大的工作范围而无法进行线性化。本文提出了一种基于Elman网络的仅由测量数据表示的柴油机建模方法。将测试台的测量结果与仿真结果进行比较表明,基于神经网络建模方法的模型可以很好地表示柴油机的动态行为。

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