State feedback predictive control for nonlinear hydro-turbine governing system
Yi, Yapeng and Zhang, Zhiwang and Chen, Diyi and Zhou, Rui and Patelli, Edoardo and Tolo, Silvia (2018) State feedback predictive control for nonlinear hydro-turbine governing system. Journal of Vibration and Control, 24 (21). pp. 4945-4959. (https://doi.org/10.1177/1077546317740013)
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Abstract
The present work introduces a novel predictive control strategy for the analysis of the dynamic performance of hydro-turbine governing systems based on fuzzy logic. Firstly, a six-dimensional nonlinear dynamic model of the system is defined. The defined model is applied to a realistic case-study, aiming to investigate the dynamic behavior of the system. In order to deal effectively with the nonlinearity of the system under study, the Takagi–Sugeno fuzzy approach is adopted. The results demonstrated through the use of the discrete Lyapunov function and Schur complements of matrices suggest that the closed-cycle control system can achieve a global asymptotic stability state. The second part focuses on the quantification of the impact of sudden changes in operating conditions on the overall performance. The numerical results indicate that the proposed predictive control method can ensure the performance of the system to be reliable and robust to external inferences. In addition to this, the approach proposed has unquestionable advantages over the traditional proportional–integral–derivative and model predictive controllers with regard to nonlinear systems applications.
ORCID iDs
Yi, Yapeng, Zhang, Zhiwang, Chen, Diyi, Zhou, Rui, Patelli, Edoardo ORCID: https://orcid.org/0000-0002-5007-7247 and Tolo, Silvia;-
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Item type: Article ID code: 70895 Dates: DateEvent1 November 2018Published19 November 2017Published Online2 October 2017AcceptedSubjects: Science > Mathematics
Technology > Mechanical engineering and machineryDepartment: Faculty of Engineering > Civil and Environmental Engineering Depositing user: Pure Administrator Date deposited: 13 Dec 2019 17:35 Last modified: 11 Nov 2024 12:29 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/70895