Abstract

(1)Background. For chemical processes, due to external or internal factors, the system characteristic will not remain unchanged, and the reversal characteristic is a typical case where the system characteristic will change to the opposite characteristic. In this work, the reverse characteristic can be considered to consist of two opposite characteristics, in other words, the relationship between input and output consists of two opposite relationships. As the input increases or decreases, the system characteristics will change, when the input exceeds a certain value, the original system characteristic will even become opposite to the original. Then, for the control loop, the negative feedback becomes positive feedback and the system will be unstable, then, the working condition changes from normal to abnormal, which threatens the safety of chemical processes. Thus, it is urgent to monitor and eliminate this abnormal situation with reversal characteristic. However, traditional monitoring strategies cannot monitor the change of system characteristic and determine when the system characteristic is reversed, and there are still no effective process recovery methods aiming at restoring the system performance from such an abnormal situation. (2)Methods. To provide effective monitoring for the abnormal situation with reversal characteristic, the local monitoring strategy based on the long-short time window was proposed. Then, to avoid accidents and restore the system performance automatically, the first scheme of self-recovery, in which the dual control was used to improve system characteristic and the switching control was used to make the control loop be negative feedback but did not accumulate the changes of input, was proposed. Furthermore, to make up for the detection delay and increase the impact on the system, the changes of input were accumulated to form the second scheme of self-recovery. To verify the effectiveness of the proposed method, the abnormal situation with reversal characteristic was introduced and constructed in the Tennessee Eastman (TE) process. (3)Significant Findings. The case study on the numerical example and the TE process shows that the abnormal situation with reversal characteristic did exist and was well constructed; the long-short time window based local monitoring strategy can effectively reflect the change of the system characteristic and determine when the system characteristic was reversed; both the first and second schemes of self-recovery can eliminate this abnormal situation and restore the system performance automatically, but the second scheme had a better effect because it can reduce the switching times and make the system return to normal faster; and the dual control was an effective tool to improve the system performance. In addition, the discussion of window width showed that when the width of the long time window was twice that of the short time window, the performance of the self-recovery scheme was the best.

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