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Distributed data-based fault identification and accommodation in networked process systems

机译:网络过程系统中基于数据的分布式故障识别和处理

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This paper presents a data-based framework for distributed actuator fault identification and accommodation in networked process systems controlled over a resource-constrained communication medium. Initially, a quasi-decentralized networked control structure is designed to stabilize the plant in the absence of faults. The structure consists of a set of local model-based control systems that communicate with one another at discrete times. An explicit characterization of the networked closed-loop stability region is obtained in terms of the update period, the accuracy of the models, and the choice of controller design parameters. To address the actuator fault identification problem, a set of local fault diagnosis agents are designed and embedded within the various subsystems. Each agent uses a moving-horizon parameter estimation scheme to estimate on-line the size and location of the local faults using the locally sampled states and the model state estimates for the interconnected units. Potential discrepancies or ambiguities in the local fault diagnosis results, which may be caused by the strong dynamic coupling between the individual subsystems and the presence of plant-model mismatch, are reconciled by means of a fault estimation confidence interval which is obtained by analyzing the networked closed-loop dynamics at update times. Once the locations and magnitudes of the actuator faults are identified, the resulting estimates are transmitted to a higher-level supervisor to select and implement a suitable fault accommodation strategy. A number of stability-preserving fault accommodation strategies are devised, including updating the post-fault models, adjusting the controllers' parameters, or a combination of both. The selection of the appropriate fault accommodation strategy is made on the basis of the estimated fault magnitude and the characterization of the networked closed-loop stability region. Finally, the developed methodology is illustrated using a reactor-separator process example subject to both sudden and incipient control actuator faults. (C) 2015 Elsevier Ltd. All rights reserved.
机译:本文提出了一个基于数据的框架,用于在资源受限的通信介质上控制的网络过程系统中的分布式执行器故障识别和处理。最初,拟分散网络控制结构旨在在无故障的情况下稳定工厂。该结构由一组基于局部模型的控制系统组成,这些控制系统在离散时间相互通信。根据更新周期,模型的准确性以及控制器设计参数的选择,可以得到网络闭环稳定性区域的明确特征。为了解决执行器故障识别问题,设计了一组本地故障诊断代理,并将其嵌入各个子系统中。每个代理使用移动水平参数估计方案,以使用局部采样状态和互连单元的模型状态估计值在线估计局部故障的大小和位置。通过分析网络获得的故障估计置信区间,可以解决由局部子系统之间强大的动态耦合和工厂模型不匹配的存在所引起的局部故障诊断结果中的潜在差异或歧义。更新时的闭环动态。一旦确定了执行器故障的位置和严重程度,就将估算结果传送给更高级别的主管,以选择并实施合适的故障处理策略。设计了许多保持稳定性的故障适应策略,包括更新故障后模型,调整控制器参数或两者结合。根据估计的故障量和网络闭环稳定区域的特征,选择合适的故障处理策略。最后,使用反应堆-分离器工艺实例说明了所开发的方法,该实例受突然和初始控制致动器故障的影响。 (C)2015 Elsevier Ltd.保留所有权利。

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