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Model-Based Control of a Nonlinear Aircraft Engine Simulation using an Optimal Tuner Kalman Filter Approach

机译:基于最优调谐器卡尔曼滤波方法的非线性飞机发动机仿真的基于模型的控制

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This paper covers the development of a model-based engine control (MBEC) methodology featuring a self tuning on-board model applied to an aircraft turbofan engine simulation. Here, the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS40k) serves as the MBEC application engine. CMAPSS40k is capable of modeling realistic engine performance, allowing for a verification of the MBEC over a wide range of operating points. The on-board model is a piece-wise linear model derived from CMAPSS40k and updated using an optimal tuner Kalman Filter (OTKF) estimation routine, which enables the on-board model to self-tune to account for engine performance variations. The focus here is on developing a methodology for MBEC with direct control of estimated parameters of interest such as thrust and stall margins. Investigations using the MBEC to provide a stall margin limit for the controller protection logic are presented that could provide benefits over a simple acceleration schedule that is currently used in traditional engine control architectures.
机译:本文涵盖了基于模型的发动机控制(MBEC)方法的开发,该方法具有适用于飞机涡扇发动机仿真的自调整机载模型。在这里,商业模块化航空推进系统仿真40,000(CMAPSS40k)用作MBEC应用引擎。 CMAPSS40k能够对逼真的发动机性能进行建模,从而可以在广泛的工作点上对MBEC进行验证。车载模型是从CMAPSS40k导出的分段线性模型,并使用最佳调谐器卡尔曼滤波器(OTKF)估计例程进行了更新,该模型使车载模型能够进行自我调整以解决发动机性能的变化。这里的重点是为MBEC开发一种方法,该方法可以直接控制感兴趣的估计参数,例如推力和失速裕度。提出了使用MBEC为控制器保护逻辑提供失速裕量限制的研究,该研究可以提供优于传统发动机控制体系结构中当前使用的简单加速时间表的好处。

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