Variable parameter resized zero attracting least mean fourth control for grid-tied pv system

This paper presents the variable parameter resized zero attracting least mean fourth (VP-RZA-LMF) control algorithm for grid-tied photovoltaic (PV) system. The proposed control algorithm is superior over the conventional control algorithms in terms of swift response and handling the irregular nature of solar irradiations. The DC bus voltage control is incorporated in voltage source converter (VSC) control. The boost converter utilizes the maximum power point tracking (MPPT) algorithm for producing its gating sequence to keep PV array voltage constant. - BEIESP

Of Discovery and Dread: The Importance of Work Challenges for International Business Travelers’ Thriving and Global Role Turnover Intentions

As frequent travel across international borders has become common for an ever‐increasing number of workers, it is essential to understand what helps these international business travelers (IBTs) thrive and embrace their global work responsibilities. This study's purpose is to examine the role of developmental opportunities (i.e., work role challenges) in helping IBTs see frequent travel as a predominantly beneficial experience. By integrating two theories of motivation—conservation of resources theory and the challenge‐hindrance demands framework—I build a moderated mediation model of IBTs’ intent to cease their global work responsibilities (i.e., global role turnover intentions). Using latent moderated structural equation modeling (LMS) I test the model on a sample of 204 IBTs collected at two time‐points. Results show that, through the psychological state of thriving at work, travel frequency has a negative indirect association with IBTs’ global role turnover intentions when IBTs’ work roles are challenging and a positive association when their work lacks challenge. This is primarily the case regarding the challenge of being responsible for others at work. The novelty of IBTs’ work tasks is also a salient challenge but to a lesser extent. This study contributes to literatures on global work, work role design, and thriving

An online position error correction method for sensorless control of permanent magnet synchronous machine with parameter mismatch

To eliminate the influence of parameter mismatch for fundamental model based sensorless methods, an effective online position error correction method is proposed for permanent magnet synchronous machines in this paper. Based on the derived position error mechanism, i.e. the error varies proportionally to the dq -axis currents, the proposed method injects a sinusoidal current signal with a small amplitude and low frequency into the d - or q -axis current for a short period. During injection, the corresponding sinusoidal response for current injection can be acquired from the estimated speed of the sensorless position observer. It is found that the amplitude of the response in the estimated speed decreases as the parameter mismatch reduces, and eventually reaches a minimum if there is no parameter mismatch. Thus, by applying the least mean square (LMS) algorithm, the amplitude of the response in the estimated speed can be minimised as the parameters are adaptively adjusted to the actual values, and then the position error can be corrected. The proposed method is validated through experiments on a permanent magnet generator drive system

The socio-economic effects of digital technologies on Australian academics and farmers

This thesis investigated the social and economic effects of digital technologies, and in particular information and communication technologies (ICTs), on the Australian academics and farmers in the context of an ongoing emphasis by the Australian government on the digital economy. I am motivated to conduct the research because politicians and scholars feel that the digital economy is a way ahead for improving the living standards of general Australians. Although a substantial research initiative has already been undertaken by previous researchers to examine the benefits of modern ICTs (information and communication technologies) in society, the extent of benefits (or problems) associated with the expansion of digital infrastructure facilities are yet to be estimated for at least two sectors of the economy – higher education and agriculture. In the given context of the Australian Government’s policy on the digital future, this thesis aims to study the effects of digital technologies, particularly ICTs, on academics and farmers in Australia. The direction of effects encompasses social and economic aspects only. I used three types of theories: affordance theory; Ajzen and Fishbein’s (1980) theory of reasoned action; and the theory of (research) production function. With regard to research methodology, I used qualitative, quantitative and a combination of both (i.e. mixed) research approaches. The data used in this study was drawn from two sources: – (i) a primary source and (ii) a secondary source. The source of the primary data was academic teaching staff members of the University of Southern Queensland, and the source of secondary data was the Australian Department of Agriculture. The thematic analysis showed that, because of the use of eLearning environments, the teaching academics at USQ perceived that their workload had increased. This was labelled as 'perceived increased workloads' in this study. From this study, three broad themes emerged. These themes were classified as temporal, pedagogical and technical limitations, and were attributed to the 'perceived workloads?' of the academics. This was the theoretical knowledge contribution of this thesis. Using factor analysis , I found evidence of both positive and negative attitudes of university academic staff members to ICTs. Next, using Ajzen and Fishbein’s (1980; 2005) theory of reasoned action, a and cross-tabulation analysis, I found that the native-English language status of the academic had a statistically significant association with the variation of attitudes to ICTs. My non-parametric regression analysis also confirmed a statistically significant relationship between the language status of the teaching academics and the variations on their attitudes to ICTs. Further, Using primary survey data and regression analysis, I found a statistically significant relationship between the teaching academics’ use of the Internet per week and their research performances. Finally, using secondary data, the theory of production of microeconomics and regression analysis, I found the relationship between Australian farmers’ expenditure for telephone facilities (a variable of CTs) and their agricultural revenue. In this study, I found a statistically significant positive relationship between the farmers’ agricultural revenue and the farmers’ expenditure on their uses of telephones. The contributions of this research to existing knowledge are as follows. From the teaching academics’ perspective, the affordances of an eLearning environment encompass pedagogical, temporal and technological limitations that contributed to the teaching academics’ 'perceived workloads'? Secondly, the empirical research supports Ajzen and Fishbein’s (1980) theory regarding the relationship between the native language status of the academics, which is a social-demographic factor, and their attitudes to using ICTs. Thirdly, the empirical research supports the idea that the Internet is an important physical factor of the research production function. The contribution of the Internet is obvious because it represents a form of digital infrastructure facility. In the future, research should model a research (or knowledge) production function that incorporates the digital capital in the production function; otherwise, the study may generate biased results because of the endogeneity problem. Fourthly, and finally, I have found that telecommunication is an important physical factor of agricultural production, which means that, similarly to manufacturing and service sectors, the agricultural sector can reap benefits from the use of digital technologies, which has been so far largely unreported in the literature. The implications of digital futures lie in a number of government initiatives directed at the university and agricultural sectors of the economy. This includes overcoming the limitations encountered by academics and expanding the national broadband network infrastructure facilities to remote Australian regions

Design of Neuromemristive Systems for Visual Information Processing

Neuromemristive systems (NMSs) are brain-inspired, adaptive computer architectures based on emerging resistive memory technology (memristors). NMSs adopt a mixed-signal design approach with closely-coupled memory and processing, resulting in high area and energy efficiencies. Previous work suggests that NMSs could even supplant conventional architectures in niche application domains such as visual information processing. However, given the infancy of the field, there are still several obstacles impeding the transition of these systems from theory to practice. This dissertation advances the state of NMS research by addressing open design problems spanning circuit, architecture, and system levels. Novel synapse, neuron, and plasticity circuits are designed to reduce NMSs’ area and power consumption by using current-mode design techniques and exploiting device variability. Circuits are designed in a 45 nm CMOS process with memristor models based on multilevel (W/Ag-chalcogenide/W) and bistable (Ag/GeS2/W) device data. Higher-level behavioral, power, area, and variability models are ported into MATLAB to accelerate the overall simulation time. The circuits designed in this work are integrated into neural network architectures for visual information processing tasks, including feature detection, clustering, and classification. Networks in the NMSs are trained with novel stochastic learning algorithms that achieve 3.5 reduction in circuit area, reduced design complexity, and exhibit similar convergence properties compared to the least-mean-squares algorithm. This work also examines the effects of device-level variations on NMS performance, which has received limited attention in previous work. The impact of device variations is reduced with a partial on-chip training methodology that enables NMSs to be configured with relatively sophisticated algorithms (e.g. resilient backpropagation), while maximizing their area-accuracy tradeoff

Machine learning and its applications in reliability analysis systems

In this thesis, we are interested in exploring some aspects of Machine Learning (ML) and its application in the Reliability Analysis systems (RAs). We begin by investigating some ML paradigms and their- techniques, go on to discuss the possible applications of ML in improving RAs performance, and lastly give guidelines of the architecture of learning RAs. Our survey of ML covers both levels of Neural Network learning and Symbolic learning. In symbolic process learning, five types of learning and their applications are discussed: rote learning, learning from instruction, learning from analogy, learning from examples, and learning from observation and discovery. The Reliability Analysis systems (RAs) presented in this thesis are mainly designed for maintaining plant safety supported by two functions: risk analysis function, i.e., failure mode effect analysis (FMEA) ; and diagnosis function, i.e., real-time fault location (RTFL). Three approaches have been discussed in creating the RAs. According to the result of our survey, we suggest currently the best design of RAs is to embed model-based RAs, i.e., MORA (as software) in a neural network based computer system (as hardware). However, there are still some improvement which can be made through the applications of Machine Learning. By implanting the 'learning element', the MORA will become learning MORA (La MORA) system, a learning Reliability Analysis system with the power of automatic knowledge acquisition and inconsistency checking, and more. To conclude our thesis, we propose an architecture of La MORA

Language, Internet and Platform Competition

The World Wide Web was originally a totally English-based medium due to its US origin. Although the presence of other languages has steadily risen, content in English is still dominant, which raises a natural question of how bilingualism of con- sumers of a home country affects production of web content in the home language and domestic welfare? In this paper, we address this question by studying how bilingual- ism affects competition between a foreign search engine and a domestic one within a small country and thereby production of home language content. We ?nd that bilingualism unambiguously softens platform competition, which in turn can induce a reduction in home language content and in home country?s welfare. In particular, it is possible that content in the foreign language crowds out so much content in the home language that consumers enjoy less content when they are bilingual than when they are monolingual

Mathematics and Digital Signal Processing

Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems

Performance Improvement of Wide-Area-Monitoring-System (WAMS) and Applications Development

Wide area monitoring system (WAMS), as an application of situation awareness, provides essential information for power system monitoring, planning, operation, and control. To fully utilize WAMS in smart grid, it is important to investigate and improve its performance, and develop advanced applications based on the data from WAMS. In this dissertation, the work on improving the WAMS performance and developing advanced applications are introduced.To improve the performance of WAMS, the work includes investigation of the impacts of measurement error and the requirements of system based on WAMS, and the solutions. PMU is one of the main sensors for WAMS. The phasor and frequency estimation algorithms implemented highly influence the performance of PMUs, and therefore the WAMS. The algorithms of PMUs are reviewed in Chapter 2. To understand how the errors impact WAMS application, different applications are investigated in Chapter 3, and their requirements of accuracy are given. In chapter 4, the error model of PMUs are developed, regarding different parameters of input signals and PMU operation conditions. The factors influence of accuracy of PMUs are analyzed in Chapter 5, including both internal and external error sources. Specifically, the impacts of increase renewables are analyzed. Based on the analysis above, a novel PMU is developed in Chapter 6, including algorithm and realization. This PMU is able to provide high accurate and fast responding measurements during both steady and dynamic state. It is potential to improve the performance of WAMS. To improve the interoperability, the C37.118.2 based data communication protocol is curtailed and realized for single-phase distribution-level PMUs, which are presented in Chapter 7.WAMS-based applications are developed and introduced in Chapter 8-10. The first application is to use the spatial and temporal characterization of power system frequency for data authentication, location estimation and the detection of cyber-attack. The second application is to detect the GPS attack on the synchronized time interval. The third application is to detect the geomagnetically induced currents (GIC) resulted from GMD and EMP-E3. These applications, benefited from the novel PMU proposed in Chapter 6, can be used to enhance the security and robust of power system