Noise-to-state exponentially stabilizing (state, input)-disturbed CSTRs with non-vanishing noise. (August 2022)

• Record Type: Journal Article
• Authors: Lu, Yafei; Fang, Zhou; Gao, Chuanhou; Dochain, Denis
• Is Part Of: Automatica. Volume 142(2022)
• Publication Date: 2022-08
• Subjects: (state, input)-disturbed CSTR -- Noise-to-state exponential stability -- Probability domain -- Time domain; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2022.110387
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: In this paper, we have proposed a (state, input)-disturbed CSTR (sidCSTR) model that considers unknown but bounded fluctuations in kinetics, flow rates, and heat exchange. A feedback control law is developed that stabilizes the sidCSTR system to reach noise-to-state exponential stability (NSES). The lower bound of the distribution for the state of the NSES sidCSTR system is analyzed both from the probability domain and the time domain. The performance and the validity of the proposed method are demonstrated using a case study dealing with a second-order reversible reaction.