This paper proposes an adaptive rotor current controller for doubly-fed induction generator (DFIG), which consists of a proportional (P) controller and two harmonic resonant (R) controllers implemented in the rotor rotating reference frame. The two resonant controllers are tuned at slip frequencies ω_slip+ and ω_slip−, respectively. As a result, the positive- and negative-sequence components of the rotor current are fully regulated by the PR controller without involving the positive- and negative-sequence decomposition, which in effect improves the fault ride-through (FRT) capability of the DFIG-based wind power generation system during the period of large transient grid voltage unbalance. Correctness of the theoretical analysis and feasibility of the proposed unbalanced control scheme are validated by simulation on a 1.5-MW DFIG wind power generation system.

This paper presents an investigation of inverter fault-tolerant operation for a permanent magnet synchronous motor (PMSM) direct torque control (DTC) system under various inverter faults. The performance of a faulty standard 6-switch inverter driven PMSM DTC system is analyzed. To avoid the loss or even disaster caused by the inverter faults, a topology-modified inverter with fault-tolerant capability is introduced, which is reconfigured as a 3-phase 4-switch inverter. The modeling of the 4-switch inverter is then analyzed and a novel DTC strategy with a unique nonlinear perpendicular flux observer and feedback compensation scheme is proposed for obtaining a continuous, disturbance-free drive system. The simulation and experimental results demonstrate that the proposed inverter fault-tolerant PMSM DTC system is able to operate stably and continuously with acceptable static and pretty good dynamic performance.

To improve the accuracy of the stator winding fault diagnosis in induction motor, a new diagnostic method based on the Hilbert-Huang transform (HHT) was proposed. The ratio of fundamental zero sequence voltage to positive sequence voltage after switch-off was selected as the stator fault characteristic, which could effectively avoid the influence of the supply unbalance and the load fluctuation, and directly represent the asymmetry in the stator. Using the empirical mode decomposition (EMD) based on HHT, the zero sequence voltage after switch-off was decomposed and the fundamental component was extracted. Then, the fault characteristic can be acquired. Experimental results on a 4-kW induction motor demonstrate the feasibility and effectiveness of this method.

Power Quality (PQ) combined disturbances become common along with ubiquity of voltage flickers and harmonics. This paper presents a novel approach to classify the different patterns of PQ combined disturbances. The classification system consists of two parts, namely the feature extraction and the automatic recognition. In the feature extraction stage, Phase Space Reconstruction (PSR), a time series analysis tool, is utilized to construct disturbance signal trajectories. For these trajectories, several indices are proposed to form the feature vectors. Support Vector Machines (SVMs) are then implemented to recognize the different patterns and to evaluate the efficiencies. The types of disturbances discussed include a combination of short-term disturbances (voltage sags, swells) and long-term disturbances (flickers, harmonics), as well as their homologous single ones. The feasibilities of the proposed approach are verified by simulation with thousands of PQ events. Comparison studies based on Wavelet Transform (WT) and Artificial Neural Network (ANN) are also reported to show its advantages.

During ground faults on transmission lines, a number of towers near the fault are likely to acquire high potentials to ground. These tower voltages, if excessive, may present a hazard to humans and animals. This paper presents analytical methods in order to determine the transmission towers potentials during ground faults, for long and short lines. The author developed a global systematic approach to calculate these voltages, which are dependent of a number of factors. Some of the most important factors are: magnitudes of fault currents, fault location with respect to the line terminals, conductor arrangement on the tower and the location of the faulted phase, the ground resistance of the faulted tower, soil resistivity, number, material and size of ground wires. The effects of these factors on the faulted tower voltages have been also examined for different types of power lines.

Cascaded multilevel converters built with integrated modules have many advantages such as increased power density, flexible distributed control, multi-functionality, increased reliability and short design cycles. However, the system performance will be affected due to the synchronization errors among each integrated modules. This paper analyzes the impact of the three kinds of synchronization errors on the whole system performance, as well as detailed synchronization implementation. Some valuable conclusions are derived from the theoretical analysis, simulations and experimental results.

A new lighting and enlargement on phase spectrogram (PS) and frequency spectrogram (FS) is presented in this paper. These representations result from the coupling of power spectrogram and short time Fourier transform (STFT). The main contribution is the construction of the 3D phase spectrogram (3DPS) and the 3D frequency spectrogram (3DFS). These new tools allow such specific test signals as small slope linear chirp, phase jump and small frequency jump to be analyzed. An application case of musical signal analysis is reported. The main objective is to detect small frequency and phase variations in order to characterize each type of sound attack without losing the amplitude information given by power spectrogram.

In this paper, the generalized bounds are derived on the partial periodic correlation of complex roots of unity sequence set with zero or low correlation zone (ZCZ/LCZ) as the important criteria of the sequence design and application. The derived bounds are with respect to family size, subsequence length, maximum partial autocorrelation sidelobe, maximum partial crosscorrelation value and the ZCZ/LCZ. The results show that the derived bounds include the previous periodic bounds, such as Sarwate bound, Welch bound, Peng-Fan bound and Paterson-Lothian bound, as special cases.

A modification of the Hill cipher algorithm was recently proposed by Ismail et al.(2006), who claimed that their new scheme could offer more security than the original one due to an extra non-linearity layer introduced via an elaborated key generation mechanism. That mechanism produces one different encryption key for each one of the plaintext blocks. Nevertheless, we show in this paper that their method still has severe security flaws whose weaknesses are essentially the same as that already found in the original Hill cipher scheme.

This paper deals with design and analysis of user scheduling and power allocation for multi-antenna OFDM systems with DPC, ZF-DPC, ZF-BF and TDMA transmit strategies. We consider the general multi-user downlink scheduling problem and power minimization with multi-user rate constraints. According to the channel state, it is shown that there is a power optimal policy which selects a subset of users in each scheduling interval. We present user selection algorithms for DPC, ZF-DPC, ZF-BF and TDMA for multi-antenna OFDM system in broadcast channels, and we also present the practical water-filling solution in this paper. By the selected users with the consideration of fairness, we derive the power optimization algorithm with multi-user rate constraints. We also analyze the power duality of uplink-downlink for the transmit strategies of DPC, ZF-DPC and ZF-BF. Simulation results show that the present user-scheduling algorithm and power minimization algorithm can achieve good power performance, and that the scheduling algorithm can guarantee fairness.

The existing H.264/AVC rate control schemes rarely include the perceptual considerations. As a result, the improvements in visual quality are hardly comparable to those in peak signal-to-noise ratio (PSNR). In this paper, we propose a perceptual importance analysis scheme to accurately abstract the spatial and temporal perceptual characteristics of video contents. Then we perform bit allocation at macroblock (MB) level by adopting a perceptual mode decision scheme, which adaptively updates the Lagrangian multiplier for mode decision according to the perceptual importance of each MB. Simulation results show that the proposed scheme can efficiently reduce bit rates without visual quality degradation.

TIRF microscopy has provided a means to view mobile granules within 100 nm in size in two dimensions. However quantitative analysis of the position and motion of those granules requires an appropriate tracking method. In this paper, we present a new tracking algorithm combined with the unique features of TIRF. Firstly a fluorescence correction procedure was processed to solve the problem of fluorescence bleaching over time. Mobile granules were then segmented from a time-lapse image stack by an adaptive background subtraction method. Kalman filter was introduced to estimate and track the granules that allowed reducing searching range and hence greater reliability in tracking process. After the tracked granules were located in x-y plane, the z-position was indirectly inferred from the changes in their intensities. In the experiments the algorithm was applied in tracking GLUT4 vesicles in living adipose cells. The results indicate that the algorithm has achieved robust estimation and tracking of the vesicles in three dimensions.

Cross-media retrieval is an interesting research topic, which seeks to remove the barriers among different modalities. To enable cross-media retrieval, it is needed to find the correlation measures between heterogeneous low-level features and to judge the semantic similarity. This paper presents a novel approach to learn cross-media correlation between visual features and auditory features for image-audio retrieval. A semi-supervised correlation preserving mapping (SSCPM) method is described to construct the isomorphic SSCPM subspace where canonical correlations between the original visual and auditory features are further preserved. Subspace optimization algorithm is proposed to improve the local image cluster and audio cluster quality in an interactive way. A unique relevance feedback strategy is developed to update the knowledge of cross-media correlation by learning from user behaviors, so retrieval performance is enhanced in a progressive manner. Experimental results show that the performance of our approach is effective.

Statistical and contextual information are typically used to detect moving regions in image sequences for a fixed camera. In this paper, we propose a fast and stable linear discriminant approach based on Gaussian Single Model (GSM) and Markov Random Field (MRF). The performance of GSM is analyzed first, and then two main improvements corresponding to the drawbacks of GSM are proposed: the latest filtered data based update scheme of the background model and the linear classification judgment rule based on spatial-temporal feature specified by MRF. Experimental results show that the proposed method runs more rapidly and accurately when compared with other methods.

Without sufficient real training data, the data driven classification algorithms based on boosting method cannot solely be utilized to applications such as the mini unmanned helicopter landmark image detection. In this paper, we propose an approach which uses a boosting algorithm with the prior knowledge for the mini unmanned helicopter landmark image detection. The stage forward stagewise additive model of boosting is analyzed, and the approach how to combine it with the prior knowledge model is presented. The approach is then applied to landmark image detection, where the multi-features are boosted to solve a series of problems, such as rotation, noises affected, etc. Results of real flight experiments demonstrate that for small training examples the boosted learning system using prior knowledge is dramatically better than the one driven by data only.

This paper investigates the exponential synchronization problem of some chaotic delayed neural networks based on the proposed general neural network model, which is the interconnection of a linear delayed dynamic system and a bounded static nonlinear operator, and covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks (CNNs), bidirectional associative memory (BAM) networks, recurrent multilayer perceptrons (RMLPs). By virtue of Lyapunov-Krasovskii stability theory and linear matrix inequality (LMI) technique, some exponential synchronization criteria are derived. Using the drive-response concept, hybrid feedback controllers are designed to synchronize two identical chaotic neural networks based on those synchronization criteria. Finally, detailed comparisons with existing results are made and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.

Among complex network models, the hierarchical network model is the one most close to such real networks as world trade web, metabolic network, WWW, actor network, and so on. It has not only the property of power-law degree distribution, but also the scaling clustering coefficient property which Barabási-Albert (BA) model does not have. BA model is a model of network growth based on growth and preferential attachment, showing the scale-free degree distribution property. In this paper, we study the evolution of cooperation on a hierarchical network model, adopting the prisoner’s dilemma (PD) game and snowdrift game (SG) as metaphors of the interplay between connected nodes. BA model provides a unifying framework for the emergence of cooperation. But interestingly, we found that on hierarchical model, there is no sign of cooperation for PD game, while the frequency of cooperation decreases as the common benefit decreases for SG. By comparing the scaling clustering coefficient properties of the hierarchical network model with that of BA model, we found that the former amplifies the effect of hubs. Considering different performances of PD game and SG on complex network, we also found that common benefit leads to cooperation in the evolution. Thus our study may shed light on the emergence of cooperation in both natural and social environments.

Battery models are of great importance to develop portable computing systems, for whether the design of low power hardware architecture or the design of battery-aware scheduling policies. In this paper, we present a physically justified iterative computing method to illustrate the discharge, recovery and charge process of Li/Li-ion batteries. The discharge and recovery processes correspond well to an existing accurate analytical battery model: R-V-W’s analytical model, and thus interpret this model algorithmically. Our method can also extend R-V-W’s model easily to accommodate the charge process. The work will help the system designers to grasp the characteristics of R-V-W’s battery model and also, enable to predict the battery behavior in the charge process in a uniform way as the discharge process and the recovery process. Experiments are performed to show the accuracy of the extended model by comparing the predicted charge times with those derived from the DUALFOIL simulations. Various profiles with different combinations of battery modes were tested. The experimental results show that the extended battery model preserves high accuracy in predicting the charge behavior.

In this letter, we introduce a novel passive transmission line of negative refractive index (i.e., left-handedness) based on identical symmetrical lattice type structures [thus called “lattice type transmission line” (LT-TL)]. The dispersion characteristic and the transmission response of the proposed LT-TL are analyzed. While all the other left-handed passive transmission lines are of high pass, the present passive left-handed transmission line is of low pass. Compared with a conventional transmission line, the LT-TL has a phase shift of 180( in the entire wide pass-band.