Fault Effect Identification-Based Adaptive Performance Self-Recovery Control Strategy for Wastewater Treatment Process

• Published in: IEEE transactions on industrial informatics Vol. 20; no. 3; pp. 3585 - 3596
• Main Authors: Du, Peihao, Zhong, Weimin, Peng, Xin, Li, Zhongmei, Li, Linlin
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.03.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuators; Adaptive control; Artificial neural networks; constraint imitation; Dissolved oxygen; Error functions; fault effect identification; Fuzzy logic; Fuzzy neural networks; Infimum; performance self-recovery control; Process control; Recovery; Sliding mode control; Uncertainty; Wastewater treatment; wastewater treatment process (WWTP)
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2023.3296878

The increasing utilization of wastewater necessitates dedicated attentions to the potential security threats, and formulate strategies for defense, response, and future protection. The nonideal actuator subject to the faults and constraints may underload the driving force and reduce the sewage purification efficiency. This article proposes an adaptive performance self-recovery control strategy for the wastewater treatment process (WWTP) with nonideal actuator. Therein, a Gaussian error function is reconstructed to imitate the asymmetrical actuator constraints. A fault effect identifier is designed to indirectly acquire fault information. Two boundary estimators are co-designed to estimate the infimum of virtual controller gain and the supremum of lumped uncertainty, respectively. The proposed control strategy can largely enhance the faulty performance self-recovery capability of the WWTP, while ensuring robust output regulation and fast convergence. Extensive experiments on dissolved oxygen control are executed on a WWTP platform to show the efficacy of the suggested control scheme.