An experimental case study of robust cascade two-element control of boiler drum level. (January 2020)

• Record Type: Journal Article
• Authors: P.U., Sunil; Desai, Khushali; Barve, Jayesh; Nataraj, P.S.V.
• Is Part Of: ISA transactions. Volume 96(2020)
• Page Start: 337
• Page End: 351
• Publication Date: 2020-01
• Subjects: Boiler-drum level control -- Drum type boilers -- Heat recovery steam generators -- Quantitative feedback theory -- Robust control; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2019.06.016
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: This paper focuses on improving the performance of boiler-drum level control over a wide range of operation using the quantitative feedback theory (QFT) approach. A lab-scale boiler that is a scaled-down version of a power plant boiler is considered for the investigations. The lab boiler has the unique advantage of inducing dynamic variations or uncertainty in system behaviour, to mimic a wide range of real-world operation scenarios. The investigations on the lab boiler are conducted as follows. Firstly, the nonlinear dynamics and uncertainty of the lab boiler over the entire operation envelope are approximated in terms of linear models with parametric variations. Then, a robust two-element QFT control system for drum level control is proposed, designed, and validated over the set of linear models. Next, the proposed QFT controller is implemented on the lab-boiler, and lastly, the performance is compared experimentally with conventional fixed and scheduled two-element control schemes. Comparison of obtained experimental results show that the proposed QFT controller scheme outperforms conventional fixed and scheduled two-element control schemes, for boiler-drum level control over a wide range of operations. Highlights: A Quantitative Feedback Theory application for robust boiler drum level control. Feasibility study on a laboratory scale natural re-circulation boiler. Control performance metric comparison with classical and schedule approach.