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首页> 外文期刊>International Journal of Control >Least costly closed-loop performance diagnosis and plant re-identification
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Least costly closed-loop performance diagnosis and plant re-identification

机译：成本最低的闭环性能诊断和工厂重新识别

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摘要

The inherent time-varying nature of dynamics in chemical processes often limits the lifetime performance of model-based control systems, as the plant and disturbance dynamics change over time. A critical step in the maintenance of model-based controllers is distinguishing control-relevant plant changes from variations in disturbance characteristics. In this paper, prediction error identification is used to evaluate a hypothesis test that detects if the performance drop arises from control-relevant plant changes. The decision rule is assessed by verifying whether an identified model of the true plant lies outside the set of all plant models that lead to adequate closed-loop performance. A unified experiment design framework is presented in the least costly context (i.e., least intrusion of nominal plant operation) to address the problem of input signal design for performance diagnosis and plant re-identification when the performance drop is due to plant changes. The application of the presented performance diagnosis approach to a (nonlinear) chemical reactor demonstrates the effectiveness of the approach in detecting the cause of an observed closed-loop performance drop based on the designed least costly diagnosis experiment.
机译：化学过程中动力学的固有时变性质通常会限制基于模型的控制系统的使用寿命，因为工厂和干扰动力学会随时间变化。维护基于模型的控制器的关键步骤是区分与控制相关的工厂变化与扰动特性的变化。在本文中，预测误差识别用于评估假设检验，该假设检验可检测性能下降是否源自与控制相关的工厂变更。通过验证所确定的真实工厂模型是否位于导致适当闭环性能的所有工厂模型集之外来评估决策规则。在成本最低的情况下（即，对标称工厂运营的侵入最少）提出了一个统一的实验设计框架，以解决由于性能变化而导致性能下降时用于性能诊断和工厂重新识别的输入信号设计问题。所提出的性能诊断方法在（非线性）化学反应器中的应用表明，该方法基于设计的成本最低的诊断实验，可以有效地检测出观察到的闭环性能下降的原因。

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