Improved Sensor Fault-Tolerant Control Technique Applied to Three-Phase Induction Motor Drive

An improved fault-tolerant control (FTC) method using mathematical functions is applied to the induction motor drive (IMD) against current sensors and speed encoder failures, which occur when the sensor is disconnected or completely damaged. The IMD with two current sensors and an encoder is speed controlled based on the field-oriented control (FOC) technique in regular operation. In this paper, an FTC unit is implemented in the FOC controller to detect and solve the sensor fault to increase the reliability of the speed control process. The measured stator currents and the feedback speed signal are integrated into the diagnosis algorithms to create a sensor fault-tolerant control function. Three diagnosis functions operating in a defined sequence are proposed for determining the health status of current and speed sensors. The FTC function performs isolation and replaces the faulty sensor signals with the proper estimated signals; then, the IMD will operate in the corresponding sensorless mode. Simulations will be performed to verify the accuracy and reliability of the proposed method under various sensor faults

An assessment of multidimensional urban poverty in Vietnam central cities

Cross section data from the Vietnam Household Living Standard Survey 2008 (VHLSS2008) was used to estimate multidimensional poverty in five urban central cities (Ha Noi, Hai Phong, Da Nang, Ho Chi Minh, and Can Tho) in Viet Nam following the methodology developed by Alkire & Santos (2010). Five dimensions of poverty were considered in the study including education, health, standard of living, economic well-being, and employment labor. The findings show that multidimensional poverty is significantly high in central cities, especially in Ho Chi Minh City. The multidimensional poor suffer from the high deprivation intensity of indicators as type of dwelling, underemployment, housing space, and working time. Moreover, five urban central cities present non-depreciable level of deprivation in electricity. Under-employment deprivation significantly increases its contribution as it receives a higher weight in the estimation. The study highlights the potential application of the methodology for national poverty measurement at multidimensional level as well as a tool for state budget allocation

Innovations in Water Management for Sustainable Development of Higher Education Institutions: Experience from Ton Duc Thang University, Vietnam

Ton Duc Thang University (TDTU), which was established in 1997, is a fully autonomous public university in Vietnam. After over 22 years of development, TDTU is now the number one university in Vietnam for all aspects. In 2019, TDTU was ranked the 1st in Vietnam and ranked 165th in the world on sustainable development by UI GreenMetric World University Rankings (UI GreenMetric). Among six categories of UI GreenMetric, including: setting and infrastructure, energy and climate change, waste, water, transport, and education, the water category of TDTU achieved 725 points out of 1000 maximum points (72.50%). This paper presents water management of TDTU, focusing on water conservation, water recycling, the use of water efficient appliances and piped water consumption. Specifically, the paper highlights innovations in water management that TDTU has implemented during the past few years. The paper concludes that sustainable water management makes great contribution to sustainable development of a higher education institutio

An Effective PSO-inspired Algorithm for Workflow Scheduling

The Cloud is a computing platform that provides on-demand access to a shared pool of configurable resources such as networks, servers and storage that can be rapidly provisioned and released with minimal management effort from clients. At its core, Cloud computing focuses on maximizing the effectiveness of the shared resources. Therefore, workflow scheduling is one of the challenges that the Cloud must tackle especially if a large number of tasks are executed on geographically distributed servers. This entails the need to adopt an effective scheduling algorithm in order to minimize task completion time (makespan). Although workflow scheduling has been the focus of many researchers, a handful efficient solutions have been proposed for Cloud computing. In this paper, we propose the LPSO, a novel algorithm for workflow scheduling problem that is based on the Particle Swarm Optimization method. Our proposed algorithm not only ensures a fast convergence but also prevents getting trapped in local extrema. We ran realistic scenarios using CloudSim and found that LPSO is superior to previously proposed algorithms and noticed that the deviation between the solution found by LPSO and the optimal solution is negligible