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The interaction between the three-phase voltage source converters (VSCs) and the power grid may cause high-frequency resonant instable problems. Studies have indicated that the non-passivity of VSCs is the main reason that leads to the resonances. The above-mentioned passive means that the equivalent output admittance of the VSC has a positive real part. In this paper, a novel damped Smith predictor is proposed to suppress the resonant instability problem that caused by time delay. The research proved that the proposed Smith predictor can significantly improve the passivity of the VSC by reducing the width of the negative real part at the high-frequencies. Simulation and experimental results demonstrate that the proposed Smith predictor can distinctly improve the robustness of the VSC.
Jiancheng Zhao; Kai Li; Xiaodong Wang; Chuan Xie; Hongbing Xu. A Novel Passivity-Based Resonant Instability Suppression Method for Grid-Connected VSC. Journal of Electrical Engineering & Technology 2020, 16, 321 -331.
AMA StyleJiancheng Zhao, Kai Li, Xiaodong Wang, Chuan Xie, Hongbing Xu. A Novel Passivity-Based Resonant Instability Suppression Method for Grid-Connected VSC. Journal of Electrical Engineering & Technology. 2020; 16 (1):321-331.
Chicago/Turabian StyleJiancheng Zhao; Kai Li; Xiaodong Wang; Chuan Xie; Hongbing Xu. 2020. "A Novel Passivity-Based Resonant Instability Suppression Method for Grid-Connected VSC." Journal of Electrical Engineering & Technology 16, no. 1: 321-331.
Due to its low conduction loss, hence high current ratings, as well as low cost, Silicon Insulated Gate Bipolar Transistor (Si IGBT) is widely used in high power applications. However, its switching frequency is generally low because of relatively large switching losses. Silicon carbide Metal-Oxide-Semiconductor Field-Effect Transistor (SiC MOSFET) is much more superior due to their fast switching speed, which is determined by the internal parasitic capacitance instead of the stored charges, like the IGBT. By the combination of SiC MOSFET and Si IGBT, this paper presents a novel series hybrid switching method to achieve IGBT’s dynamic switching loss reduction by switching under Zero Voltage Hard Current (ZVHC) turn-on and Zero Current Hard Voltage (ZCHV) turn-off conditions. Both simulation and experimental results of IGBT are carried out, which shows that the soft switching of IGBT has been achieved both in turn-on and turn-off period. Thus 90% turn-on loss and 57% turn-off loss are reduced. Two different IGBTs’ test results are also provided to study the modulation parameter’s effect on the turn-off switching loss. Furthermore, with the consideration of voltage and current transient states, a new soft switching classification is proposed. At last, another improved modulation and Highly Efficient and Reliable Inverter Concept (HERIC) inverter are given to validate the effectiveness of the device level hybrid soft switching method application.
Lan Ma; Hongbing Xu; Alex Q. Huang; Jianxiao Zou; Kai Li. IGBT Dynamic Loss Reduction through Device Level Soft Switching. Energies 2018, 11, 1182 .
AMA StyleLan Ma, Hongbing Xu, Alex Q. Huang, Jianxiao Zou, Kai Li. IGBT Dynamic Loss Reduction through Device Level Soft Switching. Energies. 2018; 11 (5):1182.
Chicago/Turabian StyleLan Ma; Hongbing Xu; Alex Q. Huang; Jianxiao Zou; Kai Li. 2018. "IGBT Dynamic Loss Reduction through Device Level Soft Switching." Energies 11, no. 5: 1182.
To overcome the performance degradation in the presence of steering vector mismatches, strict restrictions on the number of available snapshots, and numerous interferences, a novel beamforming approach based on nonlinear least-square support vector regression machine (LS-SVR) is derived in this paper. In this approach, the conventional linearly constrained minimum variance cost function used by minimum variance distortionless response (MVDR) beamformer is replaced by a squared-loss function to increase robustness in complex scenarios and provide additional control over the sidelobe level. Gaussian kernels are also used to obtain better generalization capacity. This novel approach has two highlights, one is a recursive regression procedure to estimate the weight vectors on real-time, the other is a sparse model with novelty criterion to reduce the final size of the beamformer. The analysis and simulation tests show that the proposed approach offers better noise suppression capability and achieve near optimal signal-to-interference-and-noise ratio (SINR) with a low computational burden, as compared to other recently proposed robust beamforming techniques.
Lutao Wang; Gang Jin; Zhengzhou Li; HongBin Xu. A Nonlinear Adaptive Beamforming Algorithm Based on Least Squares Support Vector Regression. Sensors 2012, 12, 12424 -12436.
AMA StyleLutao Wang, Gang Jin, Zhengzhou Li, HongBin Xu. A Nonlinear Adaptive Beamforming Algorithm Based on Least Squares Support Vector Regression. Sensors. 2012; 12 (9):12424-12436.
Chicago/Turabian StyleLutao Wang; Gang Jin; Zhengzhou Li; HongBin Xu. 2012. "A Nonlinear Adaptive Beamforming Algorithm Based on Least Squares Support Vector Regression." Sensors 12, no. 9: 12424-12436.
This paper investigates the global periodicity of cellular neural network with impulses and constant delay. Several conditions guaranteeing the existence, uniqueness, and global exponential stability of periodic solution are derived by using the continuation theorem of coincidence degree theory and suitable degenerate Lyapuniv–Krasvovskii functional.
Hui Wang; Chuandong Li; Hongbing Xu. Existence and Global Exponential Stability of Periodic Solution of Cellular Neural Networks with Delay and Impulses. Results in Mathematics 2010, 58, 191 -204.
AMA StyleHui Wang, Chuandong Li, Hongbing Xu. Existence and Global Exponential Stability of Periodic Solution of Cellular Neural Networks with Delay and Impulses. Results in Mathematics. 2010; 58 (1-2):191-204.
Chicago/Turabian StyleHui Wang; Chuandong Li; Hongbing Xu. 2010. "Existence and Global Exponential Stability of Periodic Solution of Cellular Neural Networks with Delay and Impulses." Results in Mathematics 58, no. 1-2: 191-204.