H-infinity Variable-Pitch Control for Wind Turbines Based on Takagi-Sugeno Fuzzy Theory

When the wind speed is above the rated value, the output power of the wind turbine should be maintained at the rated value in order to prevent the power generation system from overheating. In addition, the natural wind speed will fluctuate randomly in a large range of values, making the traditional control effect not ideal. This paper presents a novel H-infinity (H∞) pitch control strategy for Wind Turbine Generators (WTGs), which can make the rotor speed and output power constant when the wind speed changes in a large range. In order to shorten response time and reduce overshoot, in the specific solution, the control method combines the H∞ theory and the Takagi-Sugeno (T-S) fuzzy theory. Firstly, the linearized models of several operating points were obtained with the T-S fuzzy theory. Then, a robust controller was designed for each linear sub-system based on the H∞ control theory. Furthermore, the controllers of the sub-systems were superimposed into a global controller for the entire system through the membership function. Finally, modeling and simulation were carried out in MATLAB/SIMULINK. The simulation results show that when the wind speed changes above the rated speed, the rotor speed can be maintained at the rated value, and the output power also can be maintained at the rated value. Compared with the optimal control, the response speed of this method is faster and the overshoot is smaller. It provides a new idea for the pitch angle control of wind turbine

Optimal constant power control of wind turbine generators based on Takagi-Sugeno fuzzy model

Resource shortages and environmental pollution of the world are becoming more and more serious, wind Turbine generation as a kind of clean energy power generation has attracted much attention. The difficulty of wind power generation lies in the randomness of natural wind energy, which leads to the instability of the output power of Wind Turbine Generators (WTGs). The traditional variable pitch controller cannot realize global precision control of the wind power system. To solve the problem, this paper combines Takagi-Sugeno (T-S) fuzzy model with optimal control theory to design a robust controller. The unique novelty of the controller is that when the wind speed is higher than the rated, no matter how much the wind speed is, even if it is far from the balance point of the system, the controller can make the output power at a constant value, that is, increase the global stability of the wind power system. Specifically, the wind power system was divided into several linear subsystems, and the state feedback controller of each subsystem was designed through optimal control. Then, the subsystem controllers were merged by superposing membership functions, forming a controller of the entire system. Finally, wind turbine generators (WTGs) were modeled and simulated in Matlab/Simulink. The results show that the proposed controller kept the output power of WTGs constant under the global step wind of 13–25 m/s and the stochastic wind of 14–15 m/s. Our design enables the precision control at any wind speed, and improves the stability of power output of WTGs

H-infinity Variable-Pitch Control for Wind Turbines Based on Takagi-Sugeno Fuzzy Theory

When the wind speed is above the rated value, the output power of the wind turbine should be maintained at the rated value in order to prevent the power generation system from overheating. In addition, the natural wind speed will fluctuate randomly in a large range of values, making the traditional control effect not ideal. This paper presents a novel H-infinity (H∞) pitch control strategy for Wind Turbine Generators (WTGs), which can make the rotor speed and output power constant when the wind speed changes in a large range. In order to shorten response time and reduce overshoot, in the specific solution, the control method combines the H∞ theory and the Takagi-Sugeno (T-S) fuzzy theory. Firstly, the linearized models of several operating points were obtained with the T-S fuzzy theory. Then, a robust controller was designed for each linear sub-system based on the H∞ control theory. Furthermore, the controllers of the sub-systems were superimposed into a global controller for the entire system through the membership function. Finally, modeling and simulation were carried out in MATLAB/SIMULINK. The simulation results show that when the wind speed changes above the rated speed, the rotor speed can be maintained at the rated value, and the output power also can be maintained at the rated value. Compared with the optimal control, the response speed of this method is faster and the overshoot is smaller. It provides a new idea for the pitch angle control of wind turbine

Spatial-temporal variation in soil respiration and its controlling factors in three steppes of Stipa L. in Inner Mongolia, China

National Natural Science Foundation of China [40730105, 40673067, 40973057]; National Key Technology Research and Development Program [2007BAC03A11

Proteomic analysis to identification of hypoxia related markers in spinal tuberculosis: a study based on weighted gene co-expression network analysis and machine learning

Abstract Objective This article aims at exploring the role of hypoxia-related genes and immune cells in spinal tuberculosis and tuberculosis involving other organs. Methods In this study, label-free quantitative proteomics analysis was performed on the intervertebral discs (fibrous cartilaginous tissues) obtained from five spinal tuberculosis (TB) patients. Key proteins associated with hypoxia were identified using molecular complex detection (MCODE), weighted gene co-expression network analysis(WGCNA), least absolute shrinkage and selection operator (LASSO), and support vector machine recursive feature Elimination (SVM-REF) methods, and their diagnostic and predictive values were assessed. Immune cell correlation analysis was then performed using the Single Sample Gene Set Enrichment Analysis (ssGSEA) method. In addition, a pharmaco-transcriptomic analysis was also performed to identify targets for treatment. Results The three genes, namely proteasome 20 S subunit beta 9 (PSMB9), signal transducer and activator of transcription 1 (STAT1), and transporter 1 (TAP1), were identified in the present study. The expression of these genes was found to be particularly high in patients with spinal TB and other extrapulmonary TB, as well as in TB and multidrug-resistant TB (p-value < 0.05). They revealed high diagnostic and predictive values and were closely related to the expression of multiple immune cells (p-value < 0.05). It was inferred that the expression of PSMB9, STAT 1, and TAP1 could be regulated by different medicinal chemicals. Conclusion PSMB9, STAT1, and TAP1, might play a key role in the pathogenesis of TB, including spinal TB, and the protein product of the genes can be served as diagnostic markers and potential therapeutic target for TB