To ensure the control of the precision of air-fuel ratio(AFR)of port fuel injection(PFI)spark ignition(SI)engines,a chaos radial basis function(RBF)neural network is used to predict the air intake flow of the engine.T...To ensure the control of the precision of air-fuel ratio(AFR)of port fuel injection(PFI)spark ignition(SI)engines,a chaos radial basis function(RBF)neural network is used to predict the air intake flow of the engine.The data of air intake flow is proved to be multidimensionally nonlinear and chaotic.The RBF neural network is used to train the reconstructed phase space of the data.The chaos algorithm is employed to optimize the weights of output layer connection and the radial basis center of Gaussian function in hidden layer.The simulation results obtained from Matlab/Simulink illustrate that the model has higher accuracy compared to the conventional RBF model.The mean absolute error and the mean relative error of the chaos RBF model can reach 0.0017 and 0.48,respectively.展开更多
A comprehensive predictive strategy was proposed for the neutral-point balancing control of back-to-back three-level converters. The phase currents at both sides and the DC-link capacitor voltages were measured for th...A comprehensive predictive strategy was proposed for the neutral-point balancing control of back-to-back three-level converters. The phase currents at both sides and the DC-link capacitor voltages were measured for the prediction of the neutral-point current. A quality function was found to balance the neutral-point, and a metabolic on-times distribution factor was used as a predicator to minimize the quality function at each switching state. Simulation results show that the proposed method produces smaller ripples in tested signals compared with the established one, namely, 9.15% less in a total harmonic distortion(THD) of line-to-line voltage, 1.08% less in the THD of phase current, and 0.9 V less in the ripple of the neutral-point voltage. The obtained experimental results show that the main harmonics of the line-to-line voltage and the phase current in the proposed method are improved by 10 d B and 6 d B, respectively, and the ripple of neutral-point voltage is halved compared to the established one.展开更多
基金Project(51176014)supported by the National Natural Science Foundation of ChinaProject(2016JJ2003)supported by Natural Scienceof Hunan Province,ChinaProject(KF1605)supported by Key Laboratory of Safety Design and Reliability Technology of Engineering Vehicle in Hunan Province,China。
文摘To ensure the control of the precision of air-fuel ratio(AFR)of port fuel injection(PFI)spark ignition(SI)engines,a chaos radial basis function(RBF)neural network is used to predict the air intake flow of the engine.The data of air intake flow is proved to be multidimensionally nonlinear and chaotic.The RBF neural network is used to train the reconstructed phase space of the data.The chaos algorithm is employed to optimize the weights of output layer connection and the radial basis center of Gaussian function in hidden layer.The simulation results obtained from Matlab/Simulink illustrate that the model has higher accuracy compared to the conventional RBF model.The mean absolute error and the mean relative error of the chaos RBF model can reach 0.0017 and 0.48,respectively.
基金Project(61074018)supported by the National Natural Science Foundation of ChinaProject(2012kfjj06)supported by Hunan Province Key Laboratory of Smart Grids Operation and Control(Changsha University of Science and Technology),China
文摘A comprehensive predictive strategy was proposed for the neutral-point balancing control of back-to-back three-level converters. The phase currents at both sides and the DC-link capacitor voltages were measured for the prediction of the neutral-point current. A quality function was found to balance the neutral-point, and a metabolic on-times distribution factor was used as a predicator to minimize the quality function at each switching state. Simulation results show that the proposed method produces smaller ripples in tested signals compared with the established one, namely, 9.15% less in a total harmonic distortion(THD) of line-to-line voltage, 1.08% less in the THD of phase current, and 0.9 V less in the ripple of the neutral-point voltage. The obtained experimental results show that the main harmonics of the line-to-line voltage and the phase current in the proposed method are improved by 10 d B and 6 d B, respectively, and the ripple of neutral-point voltage is halved compared to the established one.
