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Huang, Dai-Zheng,Gong, Ren-Xi,Gong, Shu The Korean Institute of Electrical Engineers 2015 Journal of Electrical Engineering & Technology Vol.10 No.1
It is very important to make accurate forecast of wind power because of its indispensable requirement for power system stable operation. The research is to predict wind power by chaos and BP artificial neural networks (CBPANNs) method based on genetic algorithm, and to evaluate feasibility of the method of predicting wind power. A description of the method is performed. Firstly, a calculation of the largest Lyapunov exponent of the time series of wind power and a judgment of whether wind power has chaotic behavior are made. Secondly, phase space of the time series is reconstructed. Finally, the prediction model is constructed based on the best embedding dimension and best delay time to approximate the uncertain function by which the wind power is forecasted. And then an optimization of the weights and thresholds of the model is conducted by genetic algorithm (GA). And a simulation of the method and an evaluation of its effectiveness are performed. The results show that the proposed method has more accuracy than that of BP artificial neural networks (BP-ANNs).
Xie, Ling-Ling,Gong, Ren-Xi,Zhuo, Hao-Ze,Wei, Jiong-Quan The Korean Institute of Electrical Engineers 2011 Journal of Electrical Engineering & Technology Vol.6 No.4
An investigation of the mechanism of period-doubling bifurcation in a voltage mode controlled buck-boost converter operating in discontinuous conduction mode is conducted from the viewpoint of nonlinear dynamical systems. The discrete iterative model describing the dynamics of the close-loop is derived. Period-doubling bifurcation occurs at certain values of the feedback factor. Results from numerical simulations and experiments are provided to verify the evolution of perioddoubling bifurcation, and the results are consistent with the theoretical analysis. These results show that the buck-boost converters exhibit a wide range of nonlinear behavior, and the system exhibits a typical period-doubling bifurcation route to chaos under particular operating conditions.
Ling-Ling Xie,Ren-Xi Gong,Hao-Ze Zhuo,Jiong-Quan Wei 대한전기학회 2011 Journal of Electrical Engineering & Technology Vol.6 No.4
An investigation of the mechanism of period-doubling bifurcation in a voltage mode controlled buck-boost converter operating in discontinuous conduction mode is conducted from the viewpoint of nonlinear dynamical systems. The discrete iterative model describing the dynamics of the close-loop is derived. Period-doubling bifurcation occurs at certain values of the feedback factor. Results from numerical simulations and experiments are provided to verify the evolution of perioddoubling bifurcation, and the results are consistent with the theoretical analysis. These results show that the buck-boost converters exhibit a wide range of nonlinear behavior, and the system exhibits a typical period-doubling bifurcation route to chaos under particular operating conditions.
Feng, Zhao-He,Gong, Ren-Xi,Wang, Qing-Yu The Korean Institute of Electrical Engineers 2014 Journal of Electrical Engineering & Technology Vol.9 No.4
The state transition matrix are obtained by solving state equations in terms of Laplace inverse transformation and Cayley-Hamilton theorem, and an establishment of a precise discrete-iterative mapping of the voltage-fed buck-boost converter operating in discontinuous conduction mode is made. On the basis of the mapping, the converter bifurcation diagrams and Lyapunov exponent diagrams with the input voltage, the resistance, the inductance and the capacitance as the bifurcation parameters are obtained, and the effect of the parameters on the system stability is deeply studied. The results obtained show that they have a great influence on the stability of the system, and the general trend is that the increase of either the voltage-fed coefficient, input voltage or the load resistance, or the decrease of the filtering inductance, capacitance will make the system stability become poorer, and that all the parameters have a critical value, and when they are greater or less than the values, the system will go through stable 1T orbits, stable 2T orbits, 4T orbits, 8T orbits and eventually approaches chaos.
Zhao-He Feng,Ren-Xi Gong,Qing-Yu Wang 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.4
The state transition matrix are obtained by solving state equations in terms of Laplace inverse transformation and Cayley-Hamilton theorem, and an establishment of a precise discreteiterative mapping of the voltage-fed buck-boost converter operating in discontinuous conduction mode is made. On the basis of the mapping, the converter bifurcation diagrams and Lyapunov exponent diagrams with the input voltage, the resistance, the inductance and the capacitance as the bifurcation parameters are obtained, and the effect of the parameters on the system stability is deeply studied. The results obtained show that they have a great influence on the stability of the system, and the general trend is that the increase of either the voltage-fed coefficient, input voltage or the load resistance, or the decrease of the filtering inductance, capacitance will make the system stability become poorer, and that all the parameters have a critical value, and when they are greater or less than the values, the system will go through stable 1T orbits, stable 2T orbits, 4T orbits, 8T orbits and eventually approaches chaos.
Control Strategy for Buck DC/DC Converter Based on Two-dimensional Hybrid Cloud Model
Wang, Qing-Yu,Gong, Ren-Xi,Qin, Li-Wen,Feng, Zhao-He The Korean Institute of Electrical Engineers 2016 Journal of Electrical Engineering & Technology Vol.11 No.6
In order to adapt the fast dynamic performances of Buck DC/DC converter, and reduce the influence on converter performance owing to uncertain factors such as the disturbances of parameters and load, a control strategy based on two-dimensional hybrid cloud model is proposed. Firstly, two cloud models corresponding to the specific control inputs are determined by maximum determination approach, respectively, and then a control rule decided by the two cloud models is selected by a rule selector, finally, according to the reasoning structure of the rule, the control increment is calculated out by a two-dimensional hybrid cloud decision module. Both the simulation and experiment results show that the strategy can dramatically improve the dynamic performances of the converter, and enhance the adaptive ability to resist the random disturbances, and its control effect is superior to that of the current-mode control.
Control Strategy for Buck DC/DC Converter Based on Two-dimensional Hybrid Cloud Model
Qing-Yu Wang,Ren-Xi Gong,Li-Wen Qin,Zhao-He Feng 대한전기학회 2016 Journal of Electrical Engineering & Technology Vol.11 No.6
In order to adapt the fast dynamic performances of Buck DC/DC converter, and reduce the influence on converter performance owing to uncertain factors such as the disturbances of parameters and load, a control strategy based on two-dimensional hybrid cloud model is proposed. Firstly, two cloud models corresponding to the specific control inputs are determined by maximum determination approach, respectively, and then a control rule decided by the two cloud models is selected by a rule selector, finally, according to the reasoning structure of the rule, the control increment is calculated out by a two-dimensional hybrid cloud decision module. Both the simulation and experiment results show that the strategy can dramatically improve the dynamic performances of the converter, and enhance the adaptive ability to resist the random disturbances, and its control effect is superior to that of the current-mode control.
Dai-Zheng Huang,Ren-Xi Gong,Shu Gong 대한전기학회 2015 Journal of Electrical Engineering & Technology Vol.10 No.1
It is very important to make accurate forecast of wind power because of its indispensable requirement for power system stable operation. The research is to predict wind power by chaos and BP artificial neural networks (CBPANNs) method based on genetic algorithm, and to evaluate feasibility of the method of predicting wind power. A description of the method is performed. Firstly, a calculation of the largest Lyapunov exponent of the time series of wind power and a judgment of whether wind power has chaotic behavior are made. Secondly, phase space of the time series is reconstructed. Finally, the prediction model is constructed based on the best embedding dimension and best delay time to approximate the uncertain function by which the wind power is forecasted. And then an optimization of the weights and thresholds of the model is conducted by genetic algorithm (GA). And a simulation of the method and an evaluation of its effectiveness are performed. The results show that the proposed method has more accuracy than that of BP artificial neural networks (BP-ANNs).
Seroprevalence of Dirofilaria immitis in Cats from Liaoning Province, Northeastern China
Honglie Hou,Lili Cao,Wenzhi Ren,Dansheng Wang,He Ding,Juan You,Xinhua Yao,Hang Dong,Yanbing Guo,Shuxian Yuan,Xi-Chen Zhang,Pengtao Gong 대한기생충학ㆍ열대의학회 2017 The Korean Journal of Parasitology Vol.55 No.6
The present study was performed to investigate the seroprevalence and risk factors for Dirofilaria immitis infection in cats from Liaoning province, northeastern China. From October 2014 to September 2016, sera of 651 cats, including 364 domestic cats and 287 feral cats (332 females and 319 males) were assessed. They were tested for the presence of D. immitis antigen using SNAP Heartworm RT test kit. In this population, the average prevalence was 4.5%. Age and rearing conditions (feral or domestic) were found to be associated with the prevalence of D. immitis. The prevalence was significantly higher in feral cats compared with domestic cats (8.4% vs 1.4%, P<0.01). There was no significant difference between males and females (4.7% vs 4.2%, P>0.05), but older cats (≥3 years old) showed a statistically higher prevalence compared with younger cats (<3 years old) in feral populations (16.8 vs 2.4%, P<0.01), while the difference between the age groups was not statistically significant in domestic cats (2.4% vs 0.51%, P>0.05), all these results suggest that outdoor exposure time may be one of the most important factors for D. immitis prevalence in cats. Results reveal that D. immitis are prevalence in domestic and feral cats in northeastern China, which indicates that appropriate preventive measures should be taken to decrease the incidence of feline heartworm disease in Liaoning province, northeastern China.