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A Model-Based Framework for Fault Estimation and Accommodation Applied to Distributed Energy Resources

机译:基于模型的分布式能源故障估计和适应框架

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This paper presents the development and approach of a model-based fault identification and accommodation framework applied to sampled-data controlled distributed energy resources subject to control actuator faults. The main objective of the proposed approach is to handle faults that degrade stability as well as performance, while remaining robust to false alarms. The proposed method allows for dual fault detection and estimation, through the use of an embedded system model that minimizes the residual between the estimated and sampled states at each sampling period by adjusting a fault parameter in the embedded model over a past horizon. The resulting fault parameter estimate is then used by the control system to find an optimal fault accommodation strategy by minimizing a predefined performance metric whilst ensuring closed-loop stability. The developed fault accommodation framework is then applied to a simulated model of a solid oxide fuel cell subject to both stability and performance degrading faults in the control actuators. A discussion of some of the practical implementation issues associated with the developed framework is also included.
机译:本文提出了一种基于模型的故障识别和适应框架的开发方法,该框架适用于受控制执行器故障影响的采样数据控制的分布式能源。提出的方法的主要目标是处理在降低稳定性和性能的同时保持对错误警报的鲁棒性的故障。所提出的方法通过使用嵌入式系统模型实现双重故障检测和估计,该嵌入式系统模型通过在过去的水平上调整嵌入式模型中的故障参数来最小化每个采样周期在估计状态和采样状态之间的残差。然后,控制系统使用所得的故障参数估计值,通过在确保闭环稳定性的同时最小化预定义的性能指标来找到最佳的故障适应策略。然后,将开发的故障适应框架应用于固体氧化物燃料电池的模拟模型,该模型会同时受到控制执行器中稳定性和性能下降故障的影响。还包括与已开发框架相关的一些实际实施问题的讨论。

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