High bandwidth voltage and current control design for voltage source converters

In this paper, two different high bandwidth converter control strategies are discussed. One of the strategies is for voltage control and the other is for current control. The converter, in each of the cases, is equipped with an output passive filter. For the voltage controller, the converter is equipped with an LC filter, while an output has an LCL filter for current controller. The important aspect that has been discussed the paper is to avoid computation of unnecessary references using high-pass filters in the feedback loop. The stability of the overall system, including the high-pass filters, has been analyzed. The choice of filter parameters is crucial for achieving desirable system performance. In this paper, the bandwidth of achievable performance is presented through frequency (Bode) plot of the system gains. It has been illustrated that the proposed controllers are capable of tracking fundamental frequency components along with low-order harmonic components. Extensive simulation results are presented to validate the control concepts presented in the paper.

Efficient articulated trajectory reconstruction using dynamic programming and filters

This paper considers the problem of reconstructing the motion of a 3D articulated tree from 2D point correspondences subject to some temporal prior. Hitherto, smooth motion has been encouraged using a trajectory basis, yielding a hard combinatorial problem with time complexity growing exponentially in the number of frames. Branch and bound strategies have previously attempted to curb this complexity whilst maintaining global optimality. However, they provide no guarantee of being more efficient than exhaustive search. Inspired by recent work which reconstructs general trajectories using compact high-pass filters, we develop a dynamic programming approach which scales linearly in the number of frames, leveraging the intrinsically local nature of filter interactions. Extension to affine projection enables reconstruction without estimating cameras.

An analysis on the possibility of using capacitors of a three-level capacitor clamped inverter as power smoothing elements for wind power systems

This paper presents a new direct integration scheme for supercapacitors that are used to mitigate short term power fluctuations in wind power systems. The idea is to replace ordinary capacitors of a 3-level flying capacitor inverter by supercapacitors and operate them under variable voltage conditions. This approach eliminates the need of interfacing dc-dc converters for supercapacitor integration and thus considerably improves the overall efficiency. However, the major problem of this unique system is the change of supercapacitor voltages. An analysis on the effects of these voltage variations are presented. A space vector modulation method, built from the scratch, is proposed to generate undistorted current even in the presence of dynamic changes in supercapacitor voltages. A supercapacitor voltage equalisation algorithm is also proposed. Furthermore, resistive behavior of supercapacitors at high frequencies and the need for a low pass filter are highlighted. Simulation results are presented to verify the efficacy of the proposed system in suppressing short term wind power fluctuations.

Digit recognition using trispectral features

Features derived from the trispectra of DFT magnitude slices are used for multi-font digit recognition. These features are insensitive to translation, rotation, or scaling of the input. They are also robust to noise. Classification accuracy tests were conducted on a common data base of 256× 256 pixel bilevel images of digits in 9 fonts. Randomly rotated and translated noisy versions were used for training and testing. The results indicate that the trispectral features are better than moment invariants and affine moment invariants. They achieve a classification accuracy of 95% compared to about 81% for Hu's (1962) moment invariants and 39% for the Flusser and Suk (1994) affine moment invariants on the same data in the presence of 1% impulse noise using a 1-NN classifier. For comparison, a multilayer perceptron with no normalization for rotations and translations yields 34% accuracy on 16× 16 pixel low-pass filtered and decimated versions of the same data.

General trajectory prior for non-rigid reconstruction

Trajectory basis Non-Rigid Structure From Motion (NRSFM) currently faces two problems: the limit of reconstructability and the need to tune the basis size for different sequences. This paper provides a novel theoretical bound on 3D reconstruction error, arguing that the existing definition of reconstructability is fundamentally flawed in that it fails to consider system condition. This insight motivates a novel strategy whereby the trajectory's response to a set of high-pass filters is minimised. The new approach eliminates the need to tune the basis size and is more efficient for long sequences. Additionally, the truncated DCT basis is shown to have a dual interpretation as a high-pass filter. The success of trajectory filter reconstruction is demonstrated quantitatively on synthetic projections of real motion capture sequences and qualitatively on real image sequences.

A nanometre-scale non-periodic structural variation in high temperature superconducting ceramics and the implications for properties

Non-periodic structural variation has been found in the high Tc cuprates, YBa2Cu3O7-x and Hg0.67Pb0.33Ba2Ca2Cu 3O8+δ, by image analysis of high resolution transmission electron microscope (HRTEM) images. We use two methods for analysis of the HRTEM images. The first method is a means for measuring the bending of lattice fringes at twin planes. The second method is a low-pass filter technique which enhances information contained by diffuse-scattered electrons and reveals what appears to be an interference effect between domains of differing lattice parameter in the top and bottom of the thin foil. We believe that these methods of image analysis could be usefully applied to the many thousands of HRTEM images that have been collected by other workers in the high temperature superconductor field. This work provides direct structural evidence for phase separation in high Tc cuprates, and gives support to recent stripes models that have been proposed to explain various angle resolved photoelectron spectroscopy and nuclear magnetic resonance data. We believe that the structural variation is a response to an opening of an electronic solubility gap where holes are not uniformly distributed in the material but are confined to metallic stripes. Optimum doping may occur as a consequence of the diffuse boundaries between stripes which arise from spinodal decomposition. Theoretical ideas about the high Tc cuprates which treat the cuprates as homogeneous may need to be modified in order to take account of this type of structural variation.

A high cell count cascade full bridge converter for wide bandwidth ultrasonic transducer excitation

A nine level modular multilevel cascade converter (MMCC) based on four full bridge cells is shown driving a piezoelectric ultrasonic transducer at 71 and 39 kHz, in simulation and experimentally. The modular cells are small stackable PCBs, each with two fully integrated surface mount 22 V, 40 A MOSFET half-bridge converters, and include all control signal and power isolation. In this work, the bridges operate at 12 V and 384 kHz, to deliver a 96 Vpp 9 level waveform with an effective switching frequency of 3 MHz. A 9 pH air cored inductor forms a low pass filter in conjunction with the 3000 pF capacitance of the transducer load. Eight equally phase-displaced naturally sampled pulse width modulation (PWM) drive signals, along with the modulating sinusoid, are generated using phase accumulation techniques in a dedicated FPGA. Experimental time domain and FFT plots of the multilevel and transducer output waveforms are presented and discussed.

Low moisture mud from solid bowl decanters

The high moisture content of mill mud (typically 75–80% for Australian factories) results in high transportation costs for the redistribution of mud onto cane farms. The high transportation cost relative to the nutrient value of the mill mud results in many milling companies subsidising the cost of this recycle to ensure a wide distribution across the cane supply area. An average mill would generate about 100 000 t of mud (at 75% moisture) in a crushing season. The development of mud processing facilities that will produce a low moisture mud that can be effectively incorporated into cane land with existing or modified spreading equipment will improve the cost efficiency of mud redistribution to farms; provide an economical fertiliser alternative to more farms in the supply area; and reduce the potential for adverse environmental impacts from farms. A research investigation assessing solid bowl decanter centrifuges to produce low moisture mud with low residual pol was undertaken and the results compared to the performance of existing rotary vacuum filters in factory trials. The decanters were operated on filter mud feed in parallel with the rotary vacuum filters to allow comparisons of performance. Samples of feed, mud product and filtrate were analysed to provide performance indicators. The decanter centrifuge could produce mud cakes with very low moistures and residual pol levels. Spreading trials in cane fields indicated that the dry cake could be spread easily by standard mud trucks and by trucks designed specifically to spread fertiliser.

Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

Fat and thin adaptive HMM filters for vision based detection of moving targets

Computer vision is an attractive solution for uninhabited aerial vehicle (UAV) collision avoidance, due to the low weight, size and power requirements of hardware. A two-stage paradigm has emerged in the literature for detection and tracking of dim targets in images, comprising of spatial preprocessing, followed by temporal filtering. In this paper, we investigate a hidden Markov model (HMM) based temporal filtering approach. Specifically, we propose an adaptive HMM filter, in which the variance of model parameters is refined as the quality of the target estimate improves. Filters with high variance (fat filters) are used for target acquisition, and filters with low variance (thin filters) are used for target tracking. The adaptive filter is tested in simulation and with real data (video of a collision-course aircraft). Our test results demonstrate that our adaptive filtering approach has improved tracking performance, and provides an estimate of target heading not present in previous HMM filtering approaches.

A yellow filter improves response times to low-contrast targets and traffic hazards

Purpose Anecdotal evidence suggests that some sunglass users prefer yellow tints for outdoor activities, such as driving, and research has suggested that such tints improve the apparent contrast and brightness of real-world objects. The aim of this study was to establish whether yellow filters resulted in objective improvements in performance for visual tasks relevant to driving. Methods Response times of nine young (age [mean ± SD], 31.4 ± 6.7 years) and nine older (age, [mean ± SD], 74.6 ± 4.8) adults were measured using video presentations of traffic hazards (driving hazard perception task) and a simple low-contrast grating appeared at random peripheral locations on a computer screen. Response times were compared when participants wore a yellow filter (with and without a linear polarizer) versus a neutral density filter (with and without a linear polarizer). All lens combinations were matched to have similar luminance transmittances (˜27%). Results In the driving hazard perception task, the young but not the older participants responded significantly more rapidly to hazards when wearing a yellow filter than with a luminance-matched neutral density filter (mean difference, 450 milliseconds). In the low-contrast grating task, younger participants also responded more quickly for the yellow filter condition but only when combined with a polarizer. Although response times increased with increasing stimulus eccentricity for the low-contrast grating task, for the younger participants, this slowing of response times with increased eccentricity was reduced in the presence of a yellow filter, indicating that perception of more peripheral objects may be improved by this filter combination. Conclusions Yellow filters improve response times for younger adults for visual tasks relevant to driving.

Electron/ion energy loss to discharge walls revised : a case study in low-temperature, thermally nonequilibrium plasmas

Reliable calculations of the electron/ion energy losses in low-pressure thermally nonequilibrium low-temperature plasmas are indispensable for predictive modeling related to numerous applications of such discharges. The commonly used simplified approaches to calculation of electron/ion energy losses to the chamber walls use a number of simplifying assumptions that often do not account for the details of the prevailing electron energy distribution function (EEDF) and overestimate the contributions of the electron losses to the walls. By direct measurements of the EEDF and careful calculation of contributions of the plasma electrons in low-pressure inductively coupled plasmas, it is shown that the actual losses of kinetic energy of the electrons and ions strongly depend on the EEDF. It is revealed that the overestimates of the total electron/ion energy losses to the walls caused by improper assumptions about the prevailing EEDF and about the ability of the electrons to pass through the repulsive potential of the wall may lead to significant overestimates that are typically in the range between 9 and 32%. These results are particularly important for the development of power-saving strategies for operation of low-temperature, low-pressure gas discharges in diverse applications that require reasonably low power densities. © 2008 American Institute of Physics.

Alive SMC^2: Bayesian model selection for low-count time series models with intractable likelihoods

In this paper we present a new method for performing Bayesian parameter inference and model choice for low count time series models with intractable likelihoods. The method involves incorporating an alive particle filter within a sequential Monte Carlo (SMC) algorithm to create a novel pseudo-marginal algorithm, which we refer to as alive SMC^2. The advantages of this approach over competing approaches is that it is naturally adaptive, it does not involve between-model proposals required in reversible jump Markov chain Monte Carlo and does not rely on potentially rough approximations. The algorithm is demonstrated on Markov process and integer autoregressive moving average models applied to real biological datasets of hospital-acquired pathogen incidence, animal health time series and the cumulative number of poison disease cases in mule deer.