Driven by the increasing industrial demands for process safety and product quality, this paper is devoted to operational performance monitoring and performance degradation recovery for closed-loop control systems under abnormal working conditions. To this end, a new operational performance indicator is designed and its benchmark with an explicit sensitivity criteria for selecting historical data, to detect the system degradation timely and accurately. Then, by embedding the operational performance indicator as a trigger condition, a data-driven performance degradation recovery method with the aid of iterative adaptive dynamic programming (ADP) algorithm is investigated. This implementation shows that iterative ADP can be applied efficiently by utilizing both value iteration and measurement data to recover the anomaly induced system performance degradation. Finally, a case study on the continuous stirred tank reactor system is provided to validate the effectiveness of these proposed methods.
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