Reconfigurable control of Aircraft undergoing Sensor and Actuator Failure

Significant number of fatal aircraft accidents in recent years have been linked to component failures. With the predicted increase in air traffic these numbers are likely to increase. With reduction of fatal accidents as motivation, this dissertation investigates design of fault tolerant control systems for aircrafts undergoing sensor and/or actuator failures. Given that the nominal controller may perform inadequately in the event of sensors and/or actuator failure, the feasible approach for such a control scheme is to predesign various controllers anticipating these failures and then switching to an appropriate controller when the failure occurs. This is enabled by the available redundancy in sensing and actuation and allows the system to perform adequately even when these failures occur. The predesign of controllers for sensor and actuator failures is considered. Sensor failures are easily accommodated if certain detectability conditions are met. However, the predesign for actuator failures is not trivial as the position at which the actuators fail is not known a priori. It is shown that this problem can be tackled by reducing it to the classical control problem of disturbance decoupling, in which, the functional control enables the steady state output of dynamical system to reject any disturbance due to the failed actuators. For linear systems, conditions for existence of a controller capable of accommodating these failures can be understood in geometric terms and calculations are linked to solvability of coupled matrix equations. Although control design for aircrafts is done using linear techniques, failures can cause excursions into nonlinear regimes due to ensuing changes in the flight conditions. This dissertation also uses the recent results in the nonlinear regulator theory to address actuator failures in nonlinear systems. The utility of design techniques is illustrated using flight control examples with failures. The symbolic computational tools are developed and are available in the appended disk. A section on the use of variable structure servomechanisms to perform the regulation needed in case of actuator failures is also included.Ph.D., Mechanical Engineering -- Drexel University, 200

Real-Time Data Analytics for Monitoring Electricity Consumption Using IoT Technology

Rising electricity bills as a result of climate variability and new home electrical and electronic appliances are becoming a major source of concern for most end users. Consumers are typically unaware of their household electricity consumption patterns and the costs associated with them, making proper planning and budgeting difficult. Monitoring and controlling energy consumption on appliances can reduce energy costs for end-users. The Internet of Things (IoT) has the potential to provide remote monitoring and control of devices via automated monitoring and control. In this study, we propose an IoT-enabled system for monitoring and controlling energy consumption in homes to save money and make electricity more affordable to low-income people. Autonomous sensor nodes attached to power outlets collect and route power consumption data to the GSM-enabled gateway. Data aggregation is performed by the gateway for data received from all end-nodes within its coverage area. The gateway sends the data to the cloud, where real-time data analytics is performed. We also developed an algorithm that enables users to not only understand their usage patterns but also remotely control their appliances at any time. Mobile phones are used to remotely turn on and off household appliances via a machine-to-machine interface, as well as to provide real-time visualization of household energy consumption patterns

AN OVERVIEW OF INDIAN NOVEL TRADITIONAL MEDICINAL PLANTS WITH ANTI-DIABETIC POTENTIALS

Diabetes mellitus is a global metabolic epidemic affecting essential biochemical activities in almost every age group. Indian literatures like Ayurveda have already mentioned herbal remediation for a number of human ailments. Among Indian traditional medicinal plants several potential anti-diabetic plants and herbs are being used as part of our diet since prehistoric time. India has a long list of native medicinal plants with confirmed blood sugar lowering property. Some of these have proved remarkable for cure of diabetes and its complications. The current paper is aimed at providing a review on clinical and experimental studies carried out on the most effective and commonly used hypoglycemic plants and herbs species from traditional Indian flora. This write–up includes hypoglycemic and anti-hyperglycemic activities of plants, active hypoglycemic compounds and constituents along with their available toxicity status

Deep phenotyping and genomic data from a nationally representative study on dementia in India

The Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD) is a nationally representative in-depth study of cognitive aging and dementia. We present a publicly available dataset of harmonized cognitive measures of 4,096 adults 60 years of age and older in India, collected across 18 states and union territories. Blood samples were obtained to carry out whole blood and serum-based assays. Results are included in a venous blood specimen datafile that can be linked to the Harmonized LASI-DAD dataset. A global screening array of 960 LASI-DAD respondents is also publicly available for download, in addition to neuroimaging data on 137 LASI-DAD participants. Altogether, these datasets provide comprehensive information on older adults in India that allow researchers to further understand risk factors associated with cognitive impairment and dementia.Peer reviewe

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Improvement of Classical Wavelet Network over ANN in Image Compression

Image compression is the technique which reduces the amount of data required to represent a digital image. Statistical properties of the image are used in design an appropriate compression technique. An image compression is used for compression, the good picture quality can be retrieved and also achieves better compression ratio. Also in the past few years Artificial Neural Network becomes popular in the field of image compression. The inputs to the network are the pre-processed data of original image, while the outputs are reconstructed image data, which are close to the inputs. By implementing the proposed scheme the influence of different compression ratios within the scheme is investigated. It has been demonstrated through several experiments to develop a better quality of image compression techniques using Multi-Layer Perceptron (MLP) with wavelet transform coefficients and report its application to image compression by using error metrics like Mean Square Error (MSE) and Peak-Signal-to-Noise Ratio (PSNR)