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Robust residual generation for diagnosis including a reference model for residual behavior

机译:用于诊断的强大残差生成,包括残差行为的参考模型

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摘要

The main goal when synthesizing robust residual generators for diagnosis and supervision is to attenuate influence from model uncertainty on the residual while keeping fault detection performance. Without considering structural constraints of the model, it is easy to form unrealistic performance demands, and it is shown by examples how this can lead to a design with unnecessary poor robustness properties. Guided by the examples, a new design algorithm for robust residual generators is developed. A key step is the design of a reference model incorporating structural properties, and it is shown that this leads to a consistent optimization problem avoiding unrealistic demands. The available design freedom in the developed method is explicit and intuitive, and the whole algorithm fits into the framework of standard robust H-infinity-filtering relying on established and efficient methods. The designer of a diagnosis system is thus provided with a method where it is easy to specify desired behavior without violating structural requirements. (C) 2005 Elsevier Ltd. All rights reserved.
机译:合成鲁棒残差生成器进行诊断和监督的主要目的是在保持故障检测性能的同时,减轻模型不确定性对残差的影响。在不考虑模型的结构约束的情况下,很容易形成不切实际的性能需求,并通过示例说明了这如何导致具有不必要的不​​良鲁棒性的设计。在实例的指导下,开发了一种用于鲁棒残差生成器的新设计算法。关键步骤是设计包含结构特性的参考模型,结果表明,这会导致一致的优化问题,从而避免不切实际的需求。所开发方法中可用的设计自由是明确而直观的,并且整个算法都依赖于已建立且有效的方法,适用于标准鲁棒H无限滤波的框架。因此,为诊断系统的设计者提供了一种方法,在该方法中可以轻松指定所需的行为而不会违反结构要求。 (C)2005 Elsevier Ltd.保留所有权利。

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