Optimized Takagi–Sugeno Fuzzy Mixed H 2 / H ∞ Robust Controller Design Based on CPSOGSA Optimization Algorithm for Hydraulic Turbine Governing System

Lisheng Li, Jing Qian, Yidong Zou, Danning Tian, Yun Zeng, Fei Cao and Xiang Li
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Lisheng Li: School of Metallurgy and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, China
Jing Qian: School of Metallurgy and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, China
Yidong Zou: School of Metallurgy and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, China
Danning Tian: School of Global Public Health, New York University, New York, NY 10012, USA
Yun Zeng: School of Metallurgy and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, China
Fei Cao: School of Metallurgy and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, China
Xiang Li: School of Metallurgy and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, China

Energies, 2022, vol. 15, issue 13, 1-31

Abstract: The hydraulic turbine governing system (HTGS) is a complex nonlinear system that regulates the rotational speed and power of a hydro-generator set. In this work, an incremental form of an HTGS nonlinear model was established and the Takagi–Sugeno (T-S) fuzzy linearization and mixed H 2 / H ∞ robust control theory was applied to the design of an HTGS controller. A T-S fuzzy H 2 / H ∞ controller for an HTGS based on modified hybrid particle swarm optimization and gravitational search algorithm integrated with chaotic maps (CPSOGSA) is proposed in this paper. The T-S fuzzy model of an HTGS that integrates multiple-state space equations was established by linearizing numerous equilibrium points. The linear matrix inequality (LMI) toolbox in MATLAB was used to solve the mixed H 2 / H ∞ feedback coefficients using the CPSOGSA intelligent algorithm to optimize the weighting matrix in the process so that each mixed H 2 / H ∞ feedback coefficients in the fuzzy control were optimized under the constraints to improve the performance of the controller. The simulation results show that this method allows the HTGS to perform well in suppressing system frequency deviations. In addition, the robustness of the method to system parameter variations is also verified.

Keywords: HTGS; T-S fuzzy; mixed H 2 / H ? controller; CPSOGSA; wind power disturbances (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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