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Optimal Control of EGR System in Gasoline Engine Based on Gaussian Process

机译:基于高斯过程的汽油机EGR系统的最优控制。

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The contribution described in this paper is concentrated on the integration of exhaust gas recirculation (EGR) system into the process of combustion in an optimal manner. In practice, deriving a state-space model of this actuator is an energetic task as a result of involving some uncertain chemical reactions. To alleviate the effect of unobserved phenomena, which does not seem to be easy in modeling, an improved Gaussian Process (GP) is represented for identifying such dynamics. In this approach, practical modification in general formulation of GP is provided based on proportional feedback gain adjustment. Afterwards, the obtained model is considered for design of optimal model-based control strategy. The whole aim is focused on achieving a green economically gasoline engine by optimizing the trend of fuel consumption. Eventually, simulation results illustrate the effectiveness of proposed structure in EGR systems.
机译:本文所述的贡献集中在以最佳方式将废气再循环(EGR)系统集成到燃烧过程中。实际上,由于涉及一些不确定的化学反应,因此推导该执行器的状态空间模型是一项艰巨的任务。为了减轻未观察到的现象(在建模中似乎并不容易)的影响,提出了一种改进的高斯过程(GP),用于识别这种动力学。在这种方法中,基于比例反馈增益调整提供了GP通用公式的实际修改。然后,将获得的模型考虑用于基于模型的最优控制策略的设计。整个目标着眼于通过优化燃料消耗趋势来实现绿色经济的汽油发动机。最终,仿真结果说明了所提出的结构在EGR系统中的有效性。

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