A trend-based event-triggering fuzzy controller for the stabilizing control of a large-scale zinc roaster. (January 2021)

• Record Type: Journal Article
• Authors: Feng, Zhenxiang; Li, Yonggang; Sun, Bei; Yang, Chunhua; Zhu, Hongqiu; Chen, Zhisheng
• Is Part Of: Journal of process control. Volume 97(2021)
• Page Start: 59
• Page End: 71
• Publication Date: 2021-01
• Subjects: Zinc roasting process -- Large-scale zinc roaster -- Temperature stabilizing control -- Fuzzy logic -- Qualitative trend analysis -- Event-triggering mechanism; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2020.11.009
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract: In the zinc roasting process, the stability of the roasting temperature directly affects the product quality. However, the stabilizing control of the temperature inside a large-scale zinc roaster encounters complex process characteristics, fluctuating working conditions and delayed detection of product quality. The complex concentrate supply gives rise to fluctuations of zinc concentrate composition, which in turn affects the reaction atmosphere and working conditions. The trend of the roasting temperature, which contains abundant information on the potential change of working conditions, is underused in traditional controllers, leading to difficulties in stabilizing control of large-scale zinc roasters. In this work, a trend-based event-triggering fuzzy control strategy, incorporating qualitative trend analysis and an event-triggering mechanism in fuzzy control design, is proposed for the temperature stabilizing control of a large-scale zinc roaster. Qualitative trend analysis is adopted to extract the trend information of the roasting temperature. An embedded event-triggering mechanism can handle the underlying transition of working conditions timely. Hence, the fuzzy controller increases the utilization rate of the information contained in the temperature measurements. Experiments are conducted to evaluate the feasibility and advantages of the proposed fuzzy controller. Highlights: A fuzzy controller incorporating qualitative trend analysis strategy and event-triggering mechanism is proposed. The temperature trend is extracted by qualitative trend analysis strategy to provide a more comprehensive description of working conditions. An event-triggering strategy combined with qualitative trend analysis is designed to handle the transition of working conditions in time.