1. 研究目的与意义（文献综述）

owing to wide applications of automatic control systems in the process industries, the impacts of controller performance on industrial processes are becoming increasingly significant. consequently, controller maintenance is critical to guarantee routine operations of industrial processes. the workflow of controller maintenance generally involves the following steps: monitor operating controller performance and detect performance degradation, diagnose probable root causes of control system malfunctions, and take specific actions to resolve associated problems. in this article, a comprehensive overview of the mainstream of control loop monitoring and diagnosis is provided, and some existing problems are also analyzed and discussed. from the viewpoint of synthesizing abundant information in the context of big data, some prospective ideas and promising methods are outlined to potentially solve problems in industrial applications.

in a typical continuous process industry facility, the number of control loops can be about between 500 and 5000. in contrast to the wide applications of controllers, only a small portion of industrial controllers operates at healthy states, as pointed out by some existing investigations . it is therefore necessary to monitor industrial controllers and evaluate their closed-loop performance. however, the labor cost of manual monitoring is huge due to the large number of control loops, and thus achieving online and automated controller monitoring is an urgent demand from a practical perspective. to this aim, the technique of controller performance assessment (cpa), the objective of which is to detect performance degradation by analyzing routine closed-loop operating data, has gained considerable attention from both academia and industry in recent decades.

detection of performance degradation is a prerequisite to improve controller performance. then an important step afterwards is to diagnose probable root causes, which furnishes useful information for further maintenance. in general, possible causes of performance degradation can be enumerated as controller problems, equipment malfunctions and external disturbances. for controller problems, there is a need of intelligent guidelines about controller maintenance, and for problems like equipment malfunctions and external disturbances, it is imperative to report the corresponding faults timely such that specific actions can be taken to fix the related problems. from a pragmatic standpoint, an orient–decide–act–improve workflow should be followed, which includes the following steps

2. 研究的基本内容与方案

control loops are the most important components in automation systems, the important indicators such as product quality, operational safety, and energy consumption are directly related to the performance of the control loops. it is of great significance to monitor the deviation or degradation of the performance of control loops, as well as diagnose root-causes of poor performance. in this article, a date-driven framework for automatically assessing and monitoring the performance of control loops is studied. specially, the main contents of this article are as follows:

for performance assessment, this article implement the application of filtering and correlation analysis (fcor) and linear regression (lr) after researching on several categories of existing methods and understanding the theory and derivation of the minimum variance benchmark

for performance monitoring, two aspects of control indicators in closed-loop system are considered, namely the change speed and the timing correlation of variables. in aspect of change speed, sfa is used to extract most slowly varying components to monitor performance of closed-loop control system, and the application results of sfa on tennessee-eastman process data were analyzed.

3. 研究计划与安排

3月1日—3月14日：进一步查阅相关资料

尝试写出综述，详细了解控制器性能评价与监测的大部分方法，并从中总结出每种方法的关键及不足。

3月14日—3月25日：控制器性能评价算法

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