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Multiple-Model Adaptive Control of a Hybrid Solid Oxide Fuel Cell Gas Turbine Power Plant Simulator

机译:混合固体氧化物燃料电池燃气轮机模拟器的多模型自适应控制

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A Multiple Model Adaptive Control (MMAC) methodology is used to control the critical parameters of a Solid Oxide Fuel Cell Gas Turbine (SOFC-GT) cyberphysical simulator, capable of characterizing 300kW hybrid plants. The SOFC system is comprised of a hardware Balance of Plant (BoP) component, and a high fidelity FC model implemented in software. This study utilizes empirically derived Transfer Functions (TF) of the BoP facility to derive the multi model adaptive controller (MMAC) gains for the BoP system, based on an estimation algorithm which identifies current operating points. The MMAC technique is useful for systems having a wide operating envelope with nonlinear dynamics. The practical implementation of the adaptive methodology is presented through simulation in the MATLAB/SIMULINK environment.
机译:多模型自适应控制(MMAC)方法用于控制能够表征300kW混合电站的固体氧化物燃料电池燃气轮机(SOFC-GT)网络物理模拟器的关键参数。 SOFC系统由硬件工厂平衡(BoP)组件和以软件实现的高保真FC模型组成。这项研究基于确定当前工作点的估计算法,利用BoP设施的经验导出的传递函数(TF)来为BoP系统导出多模型自适应控制器(MMAC)增益。对于具有宽泛的非线性动态范围的系统,MMAC技术很有用。通过在MATLAB / SIMULINK环境中进行仿真,介绍了自适应方法的实际实现。

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