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Design of intelligent nonlinear robust controller for hydro-turbine governing system based on state-dynamic-measurement hybrid feedback linearization method.
- Source :
-
Renewable Energy: An International Journal . Mar2023, Vol. 204, p635-651. 17p. - Publication Year :
- 2023
-
Abstract
- Due to the stochastic grid loads and intermittent renewable energy sources in today's power grid, hydro-generator and grid system stability is increasingly dependent on the hydro-turbine governing system (HTGS). For the HTGS with external disturbances and system uncertainties, an intelligent nonlinear robust controller (INRC) based on state-dynamic-measurement feedback linearization (SDMFL) is proposed to enhance the HTGS's control performance in this paper. This strategy establishes a dynamic output function including actuator displacement, generator rotor angle, and turbine parameters. The relationship between dynamic output and control input is derived based on this function to establish the corresponding linear state-space model. Then, the mixed H 2 / H ∞ robust controller based on the linear model is designed to suppress the effects of external disturbances and system uncertainties on the system performance. In addition, the controller performance is optimized by levy flight and chaos theory-based gravitational search algorithm (LCGSA), resulting in the INRC. Simulations are performed in MATLAB, and the results are compared with the nonlinear robust controller (NRC) and PID controller. The results show that the proposed controller INRC improves the control performance of nonlinear HTGS with smaller overshoot and shorter adjustment time in all cases. • Design of nonlinear robust controller based on SDMFL method for HTGS. • Application of LCGSA algorithm for optimal tuning of NRC parameters. • Damping the speed oscillations against large fluctuations in grid power. • Excellent damping efficiency, especially, low overshoot, steady-state error, and settling time. • Study of robustness of HTGS against variations of system parameters. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09601481
- Volume :
- 204
- Database :
- Academic Search Index
- Journal :
- Renewable Energy: An International Journal
- Publication Type :
- Academic Journal
- Accession number :
- 161628597
- Full Text :
- https://doi.org/10.1016/j.renene.2023.01.019