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Sampled Data Model Predictive Idle Speed Control of Ultra-Lean Burn Hydrogen Engines

机译:稀燃氢发动机的采样数据模型预测怠速控制

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摘要

A model-based approach for the idle speed control of ultra-lean burn engines is presented. The results from model predictive control (MPC) are extended and collectively used with the existing sampled data control theory to obtain a rigorously developed idle speed control strategy. Controller is designed using MPC theory and facilitated by successive online linearizations of the nonlinear discrete-time model at each sampling instant. Simultaneously, the approximations due to the discretization of the nonlinear engine model are explicitly considered by designing the control within a previously proposed control design framework to obtain appropriate stability guarantees of an exact (unknown) discrete-time engine model. The proposed idle speed control method is experimentally validated on a prototype 6-cylinder hydrogen engine.
机译:提出了一种基于模型的超稀薄燃烧发动机怠速控制方法。扩展了模型预测控制(MPC)的结果,并与现有的采样数据控制理论一起使用,以获得经过严格开发的怠速控制策略。控制器采用MPC理论设计,并在每个采样时刻通过连续的非线性离散时间模型在线线性化来促进。同时,通过在先前提出的控制设计框架内设计控件来获得精确(未知)离散时间引擎模型的适当稳定性保证,可以明确考虑非线性引擎模型离散化引起的近似值。所提出的怠速控制方法已在原型六缸氢发动机上进行了实验验证。

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