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Wu R.,Southwest Jiaotong University | Wang Y.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Yan Z.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | He Z.,Southwest Jiaotong University | Wang L.,Southwest Jiaotong University
IEEE Transactions on Plasma Science | Year: 2013

Higher energy density makes inductive energy storage more promising than capacitive storage for pulsed power supplies in industrial and military fields. To realize high amplitude of pulsed current and relieve stress of opening switch, this paper proposes a novel inductive pulsed power supply consisting of high-temperature superconducting pulse power transformer and ZnO-based nonlinear resistor. First, working processes and laboratory setup are described in detail. Then, simulation using the software SIMPLORER is built to show major pulse characteristics and comparisons of two different nonlinear resistors. For verifying the feasibility of this mode, high-current testing is carried out and the results show that large amplitude of pulsed current 3 kA with energy transfer efficiency 60% is achieved, and the ZnO-based nonlinear resistor can help to limit the voltage of the opening switch to a small constant below its clamping value as current is interrupted. © 1973-2012 IEEE.


Lu L.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Lu L.,Southwest Jiaotong University | Zhao H.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Zhao H.,Southwest Jiaotong University
Journal of Sound and Vibration | Year: 2016

The filtered-x least mean lp-norm (FxLMP) algorithm is proven to be useful for nonlinear active noise control (NANC) systems. However, its performance deteriorates when the impulsive noises are presented in NANC systems. To surmount this shortcoming, a new nonlinear adaptive algorithm based on Volterra expansion model (VFxlogLMP) is developed in this paper, which is derived by minimizing the lp-norm of logarithmic cost. It is found that the FxLMP and VFxlogLMP require to select an appropriate value of p according to the prior information on noise characteristics, which prohibit their practical applications. Based on VFxlogLMP algorithm, we proposed a continuous lp-norm algorithm with logarithmic cost (VFxlogCLMP), which does not need the parameter selection and thresholds estimation. Benefiting from the various error norms for 1≤p≤2, it remains the robustness of VFxlogLMP. Moreover, the convergence behavior of VFxlogCLMP for moving average secondary paths and stochastic input signals is performed. Compared to the existing algorithms, two versions of the proposed algorithms have much better convergence and stability in impulsive noise environments. © 2015 Elsevier Ltd.


Shu Z.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Shu Z.,Southwest Jiaotong University | Ding N.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Ding N.,Southwest Jiaotong University | And 4 more authors.
IEEE Transactions on Industrial Electronics | Year: 2013

In this paper, a space vector pulsewidth modulation (PWM) (SVPWM) algorithm is proposed, which is in α′β′ frame with dc-link capacitor voltage equalization for diode-clamped multilevel converters (DCMCs). The α′β′ frame is a coordinate system similar to the αβ frame. In this frame, some original complex calculations are substituted by integer additions, integer subtractions, truncations, etc. It brings the time and area efficiency to fixed-point digital realization, particularly for the application in a field-programmable gate array. Meanwhile, a minimum energy property of multiple dc-link capacitors is applied as the basic principle for voltage equalization based on a capacitor current prediction algorithm. By evaluating the redundant vectors in each pulse dwelling period, the balancing algorithm chooses an optimal vector, generates the optimal PWM signals, and sustains the voltage stability. After that, an arbitrary multilevel SVPWM intellectual property core is designed and analyzed in the α′β ′ frame. At the end of this paper, a five-level DCMC-based static synchronous compensator is built and tested. The experimental results verify the balancing algorithm and the system steady-state and dynamic performances. © 2012 IEEE.


Zhao H.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Zhao H.,Southwest Jiaotong University | Wang W.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Wang W.,Southwest Jiaotong University
Chinese Control Conference, CCC | Year: 2016

Since the algorithms derived by maximum error correntropy criterion (MCC) can achieve better performance when the background noise containing non-Gaussian interference, it has been received increasing attention in recent decades. The maximum correntropy criterion is incorporated in second-order volterra (SOV) adaptive filtering in this paper. Then, a novel second-order volterra algorithm which is derived from maximum correntropy criteria is proposed, which is called MCC-SOV. Since using maximum correntropy criteria, the proposed algorithm can achieve better performance under impulsive environment. © 2016 TCCT.


Wang Z.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Wang Z.,Southwest Jiaotong University | Zhao H.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Zhao H.,Southwest Jiaotong University
Chinese Control Conference, CCC | Year: 2016

For highly noisy system, a novel subband adaptive filter, which is called improved affine projection subband adaptive filter (I-APSAF), is proposed. The proposed algorithm is obtained by reusing the past tap-weight vectors, which can achieve faster convergence compared to the existing algorithm. Simulations in an acoustic echo cancellation (AEC) context show that the I-APSAF achieves a lower steady-state misalignment than the normalized subband adaptive filter (NSAF), IMSAF, and improved normalized subband adaptive filter (INSAF). © 2016 TCCT.


Liu D.,Southwest Jiaotong University | Feng Q.,Southwest Jiaotong University | Jiang Q.,Southwest Jiaotong University | Jiang Q.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle
Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University | Year: 2010

To reduce the effect of nonlinearization on maglev gap control, the PSO (particle swarm optimization) algorithm was used to optimize the parameters of a maglev controller, and an improved algorithm was proposed based on the linear decreasing weight particle swarm optimization (LDW-PSO). In order to improve the optimization speed and convergence performance, neighborhood topologies, stagnation detection and global best perturbation were adopted to build the improved algorithm. The simulation and experiment results show that the output overshoot of an optimized PID (proportional-integral-derivative) controller based on the improved algorithm is 45% smaller than that of a traditional PID maglev controller.


Jing Y.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Zhang K.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Xiao J.,Southwest Jiaotong University
Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011 | Year: 2011

In this brief, we propose a fuzzy neural network (FNN) modeling approach which is applied for the modeling of gap sensor in the high-speed maglev train. The gap sensor plays an important role for electro-magnetic levitation system which is a critical component of high-speed maglev train. Artificial neural network is a promising area in the development of intelligent sensors. In this paper, we present a model of gap sensor based on fuzzy neural network. The proposed model based fuzzy network scheme incorporates intelligence into the sensor. The fuzzy neural network, as an inverse model compensator if connected in series to the output terminal of the gap sensor, would estimate the correct true gap in a range of temperature after proper training. We trained the network by gradient descent learning algorithm with momentum. It is revealed from the simulation studies that this gap sensor model can provide correct gap within the error less than 0.4mm over a range of temperature variations from 20 C to 80C and within 0.2mm only considering the work gap 8mm to 12mm. The experimental results show that the compensated gap signal meets the requirement of levitation control system. © 2011 IEEE.


Yu Y.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Yu Y.,Southwest Jiaotong University | Zhao H.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Zhao H.,Southwest Jiaotong University
Signal Processing | Year: 2016

This paper presents a new sign subband adaptive filter (SSAF) algorithm with an individual-weighting-factor (IWF) for each subband, instead of a common weighting factor in the original SSAF algorithm, called the IWF-SSAF. Each individual weighting factor only depends on the corresponding subband input signal power. Compared with the SSAF algorithm, the proposed approach fully utilizes the inherent decorrelating property of subband adaptive filter for colored inputs, leading to a better convergence performance. After that, to further enhance the performance of the IWF-SSAF in a sparse system, an improved proportionate IWF-SSAF (IWF-IPSSAF) algorithm is proposed. The proposed algorithms not only inherit the good robustness of sign algorithm against impulsive interferences, but also obtain a significant improvement in the performance as compared to their counterparts (i.e., SSAF and IPSSAF), in terms of the convergence rate and tracking capability. Besides, the IWF-IPSSAF algorithm has faster convergence rate than the IWF-SSAF algorithm for sparse impulse responses. Finally, the performances of two proposed algorithms are demonstrated in the system identification and the acoustic echo cancellation with double-talk. © 2015 Elsevier B.V. All rights reserved.


Mai R.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Lu L.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Li Y.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | Year: 2016

A phasor control method is employed in this paper to eliminate the circulating current caused by the parallel connected high frequency inverters. The topology of the parallel dual-inverter LCCL-based inductive power transfer (IPT) system and the cause of circulating current are analyzed in detail. Secondly, the virtual active/reactive power based on the current of the primary coil are calculated without using the phase-locked loop, the relationship between the goal of the phasor control and the virtual active/reactive power is analyzed, and then the circulating current eliminating approach is provided. The performance of the proposed approach is evaluated by the experimentation of two parallel connected high frequency inverters with 1.4 kW maximum transmission power and overall 89.82% DC-DC transmission efficiency. The experimental results demonstrate that the circulating current between the parallel connected inverters is dramatically reduced by the proposed algorithm. © 2016, The editorial office of Transaction of China Electrotechnical Society. All right reserved.


Jing Y.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Xiao J.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle | Zhang K.,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle
Transactions of the Institute of Measurement and Control | Year: 2013

The gap sensor plays an important role for a electro-magnetic levitation system, which is a critical component of high-speed maglev trains. An artificial neural network is a promising area in the development of intelligent sensors. In this paper, a radial basis function (RBF) neural network modelling approach is introduced for the compensation of the non-contact inductive gap sensor of the high-speed maglev train. As an inverse model compensator, the designed RBF-based model is connected in series to the output terminal of the gap sensor. The network is trained by using a gradient descent learning algorithm with momentum. This scheme could estimate accurately the correct air-gap distance in a wide range of temperatures. The simulation studies of this model show that it can provide a compensated gap value with an error of less than ±0.4 mm at any temperature from 20 to 80 C. In particulr, the maximum estimation error can be reduced to ±0.1 mm when the working gap varies from 8 to 12 mm. The experimental results indicate that the compensated gap signal could meet the requirements of the levitation control system. © The Author(s) 2013.

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