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.

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.

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.

Experimental and numerical analysis of the relationship between indoor and outdoor airborne particles in an operating room

This work investigated the impact of the HVAC filtration system and indoor particle sources on the relationship between indoor and outdoor airborne particle size and concentrations in an operating room. Filters with efficiency between 65% and 99.97% were used in the investigation and indoor and outdoor particle size and concentrations were measured. A balance mass model was used for the simulation of the impact of the surgical team, deposition rate, HVAC exhaust and air change rates on indoor particle concentration. The experimental results showed that high efficiency filters would not be expected to decrease the risk associated with indoor particles larger than approximately 1 µm in size because normal filters are relatively efficient for these large particles. A good fraction of outdoor particles were removed by deposition on the HVAC system surfaces and this deposition increased with particle size. For particles of 0.3-0.5 µm in diameter, particle reduction was about 23%, while for particles >10 µm the loss was about 78%. The modelling results showed that depending on the type of filter used, the surgical team generated between 93-99% of total particles, while the outdoor air contributed only 1-6%.

Accurate urban road model reconstruction from high resolution remotely sensed imagery based on Support Vector Machine and Gabor filters

In this paper, we presented an automatic system for precise urban road model reconstruction based on aerial images with high spatial resolution. The proposed approach consists of two steps: i) road surface detection and ii) road pavement marking extraction. In the first step, support vector machine (SVM) was utilized to classify the images into two categories: road and non-road. In the second step, road lane markings are further extracted on the generated road surface based on 2D Gabor filters. The experiments using several pan-sharpened aerial images of Brisbane, Queensland have validated the proposed method.

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.

Transit line passenger transmission and productiveness under high load conditions

Deterministic transit capacity analysis applies to planning, design and operational management of urban transit systems. The Transit Capacity and Quality of Service Manual (1) and Vuchic (2, 3) enable transit performance to be quantified and assessed using transit capacity and productive capacity. This paper further defines important productive performance measures of an individual transit service and transit line. Transit work (p-km) captures the transit task performed over distance. Passenger transmission (p-km/h) captures the passenger task delivered by service at speed. Transit productiveness (p-km/h) captures transit work performed over time. These measures are useful to operators in understanding their services’ or systems’ capabilities and passenger quality of service. This paper accounts for variability in utilized demand by passengers along a line and high passenger load conditions where passenger pass-up delay occurs. A hypothetical case study of an individual bus service’s operation demonstrates the usefulness of passenger transmission in comparing existing and growth scenarios. A hypothetical case study of a bus line’s operation during a peak hour window demonstrates the theory’s usefulness in examining the contribution of individual services to line productive performance. Scenarios may be assessed using this theory to benchmark or compare lines and segments, conditions, or consider improvements.

Passenger transmission and productiveness of transit lines with high loads

Deterministic transit capacity analysis applies to planning, design and operational management of urban transit systems. The Transit Capacity and Quality of Service Manual (1) and Vuchic (2, 3) enable transit performance to be quantified and assessed using transit capacity and productive capacity. This paper further defines important productive performance measures of an individual transit service and transit line. Transit work (p-km) captures the transit task performed over distance. Passenger transmission (p-km/h) captures the passenger task delivered by service at speed. Transit productiveness (p-km/h) captures transit work performed over time. These measures are useful to operators in understanding their services’ or systems’ capabilities and passenger quality of service. This paper accounts for variability in utilized demand by passengers along a line and high passenger load conditions where passenger pass-up delay occurs. A hypothetical case study of an individual bus service’s operation demonstrates the usefulness of passenger transmission in comparing existing and growth scenarios. A hypothetical case study of a bus line’s operation during a peak hour window demonstrates the theory’s usefulness in examining the contribution of individual services to line productive performance. Scenarios may be assessed using this theory to benchmark or compare lines and segments, conditions, or consider improvements.

High load transit line passenger transmission and productiveness efficiencies

Performance of urban transit systems may be quantified and assessed using transit capacity and productive capacity in planning, design and operational management activities. Bunker (4) defines important productive performance measures of an individual transit service and transit line, which are extended in this paper to quantify efficiency and operating fashion of transit services and lines. Comparison of a hypothetical bus line’s operation during a morning peak hour and daytime hour demonstrates the usefulness of productiveness efficiency and passenger transmission efficiency, passenger churn and average proportion line length traveled to the operator in understanding their services’ and lines’ productive performance, operating characteristics, and quality of service. Productiveness efficiency can flag potential pass-up activity under high load conditions, as well as ineffective resource deployment. Proportion line length traveled can directly measure operating fashion. These measures can be used to compare between lines/routes and, within a given line, various operating scenarios and time horizons to target improvements. The next research stage is investigating within-line variation using smart card passenger data and field observation of pass-ups. Insights will be used to further develop practical guidance to operators.

High load transit line passenger transmission and productiveness efficiencies

Performance of urban transit systems may be quantified and assessed using transit capacity and productive capacity in planning, design and operational management activities. Bunker (4) defines important productive performance measures of an individual transit service and transit line, which are extended in this paper to quantify efficiency and operating fashion of transit services and lines. Comparison of a hypothetical bus line’s operation during a morning peak hour and daytime hour demonstrates the usefulness of productiveness efficiency and passenger transmission efficiency, passenger churn and average proportion line length traveled to the operator in understanding their services’ and lines’ productive performance, operating characteristics, and quality of service. Productiveness efficiency can flag potential pass-up activity under high load conditions, as well as ineffective resource deployment. Proportion line length traveled can directly measure operating fashion. These measures can be used to compare between lines/routes and, within a given line, various operating scenarios and time horizons to target improvements. The next research stage is investigating within-line variation using smart card passenger data and field observation of pass-ups. Insights will be used to further develop practical guidance to operators.

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.