This paper addresses control performance monitoring (CPM) and degradation recovering in automatic control systems. It begins with a re-visit of CPM techniques and a summary of the major limitations of the existing CPM methods. They are (i) deficit in assessing control performance degradation caused by different types of disturbances and environment uncertainties, (ii) incapability for predicting performance degradation, and (iii) deficiency of efficient performance degradation recovering methods. In order to meet increasing demands of next generation automatic control systems for higher system performance, novel CPM methods have been developed in recent years, including performance assessment of control systems with deterministic disturbances and uncertainties, prediction of control performance degradation, and recovery of control performance degradation. Some of these methods and algorithms are introduced in the second part of this paper. The basis of these methods is a so-called residual centred model of feedback control systems, which allows a unified handling of control, monitoring and diagnosis in feedback control systems corrupted by disturbances and uncertainties. The focuses of these methods are on (i) introduction of the loop performance degradation index for the assessment and prediction of performance degradation in automatic control systems, (ii) predictive detection and estimation of loop performance degradation, and (iii) a data-driven performance degradation recovering scheme. The paper is concluded by a short summary of three future perspective topics, (i) prediction of economic system performance monitoring and estimation, (ii) reinforcement learning aided system performance recovery, and (iii) CPM digital twin.

本文介绍自动控制系统中的控制性能监视（CPM）和降级恢复。首先回顾CPM技术，并总结现有CPM方法的主要局限性。它们是：（i）在评估由不同类型的干扰和环境不确定性引起的控制性能下降时的缺陷；（ii）无法预测性能下降；以及（iii）有效的性能下降恢复方法的缺陷。为了满足下一代自动控制系统对更高系统性能的不断增长的需求，近年来已开发出新颖的CPM方法，包括对具有确定性干扰和不确定性的控制系统进行性能评估，对控制性能下降进行预测，以及控制性能下降的恢复。本文的第二部分介绍了其中的一些方法和算法。这些方法的基础是反馈控制系统的所谓残差中心模型，该模型可以统一处理在受干扰和不确定性破坏的反馈控制系统中进行控制，监视和诊断。这些方法的重点在于（i）引入环路性能下降指标以评估和预测自动控制系统中的性能下降；（ii）预测性检测和估计环路性能下降；以及（iii）数据驱动的性能下降恢复方案。本文以对三个未来展望主题的简短总结作为结束语：（i）经济系统绩效监测和评估的预测，