Input‐output partitioning for decentralized control has been studied extensively using various methods, including those based on relative gains and those based on relative degrees and sensitivities. These two concepts are characterizations of long‐time and short‐time input‐output response, respectively. A unifying new input‐output interaction measure, called relative time‐averaged gain, which characterizes the input‐output interactions during a time scale of interest for linear time‐invariant systems is proposed. This measure is used as a basis for community detection in the input‐output bipartite graph of a process network to produce subnetworks whose responses are weakly coupled in the time scale of interest. As such, the resulting decomposition accounts for both response characteristics and the network topology, and can be used efficiently for distributed control architecture design. In a case study, the proposed decomposition is applied to the distributed model predictive control of a reactor‐separator benchmark process. © 2018 American Institute of Chemical Engineers AIChE J, 64: 1682–1690, 2018

中文翻译：

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相对时间平均增益阵列（RTAGA），用于面向分布式控制的网络分解

用于分散控制的输入输出分区已使用各种方法进行了广泛研究，包括基于相对增益的方法以及基于相对度和灵敏度的方法。这两个概念分别是长时间和短期输入输出响应的表征。提出了一种统一的新的输入-输出相互作用度量，称为相对时间平均增益，该度量表征了线性时不变系统在感兴趣的时间尺度内的输入-输出相互作用。此度量用作过程网络的输入-输出二分图中的社区检测的基础，以产生其响应在感兴趣的时间范围内弱耦合的子网。这样，最终的分解说明了响应特征和网络拓扑，并可以有效地用于分布式控制体系结构设计。在一个案例研究中，将拟议的分解应用于反应堆-分离器基准过程的分布式模型预测控制。©2018美国化学工程师学会AIChE J，64：1682–1690，2018